From 87fb5b4234d4b9c56ac94cf7aa229c8fd7defdb0 Mon Sep 17 00:00:00 2001
From: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
Date: Mon, 8 Apr 2024 13:56:01 +0530
Subject: [PATCH 1/9] remove row=1 cond (#6532)

---
 ggml-sycl.cpp | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp
index b83881496..55a1eedb5 100644
--- a/ggml-sycl.cpp
+++ b/ggml-sycl.cpp
@@ -15776,7 +15776,7 @@ static void ggml_sycl_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1
 #ifdef GGML_SYCL_FORCE_DMMV
             const bool use_mul_mat_vec_q = false;
 #else
-            bool use_mul_mat_vec_q = min_compute_capability >= VER_4VEC && ggml_is_quantized(src0->type) && ggml_nrows(src1) == 1;
+            bool use_mul_mat_vec_q = min_compute_capability >= VER_4VEC && ggml_is_quantized(src0->type);
             use_mul_mat_vec_q = use_mul_mat_vec_q ||
                 (src0->type == GGML_TYPE_IQ2_XXS) || (src0->type == GGML_TYPE_IQ2_XS) || (src0->type == GGML_TYPE_IQ2_S) ||
                 (src0->type == GGML_TYPE_IQ3_XXS) || (src0->type == GGML_TYPE_IQ3_S) ||
@@ -15787,7 +15787,6 @@ static void ggml_sycl_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1
 #endif // GGML_SYCL_FORCE_DMMV
 
             if (use_mul_mat_vec_q) {
-                // NOTE: this kernel does not support ggml_nrows(src1) > 1
                 // GGML_SYCL_DEBUG("ggml_sycl_mul_mat ggml_sycl_op_mul_mat_vec_q path\n");
                 ggml_sycl_op_mul_mat(src0, src1, dst, ggml_sycl_op_mul_mat_vec_q, true);
             } else {

From beea6e1b16e783a0886e78dec01002a8c00db24d Mon Sep 17 00:00:00 2001
From: Jan Boon <jan.boon@kaetemi.be>
Date: Mon, 8 Apr 2024 20:43:30 +0800
Subject: [PATCH 2/9] llama : save and restore kv cache for single seq id
 (#6341)

* llama : save and restore kv cache for single seq id

* remove trailing whitespace

* respond error in case there's no space in the kv cache

* add kv seq save restore to test case

* add --slot-save-path arg to enable save restore and restrict save location

* Returning 0 for some cases, instead of asserting.

* cleanup error cases

* rename sequence state functions

* rename state get set functions

* add previous function names back in with DEPRECATED notice

* update doc

* adjust endpoints to preferred style

* fix restoring zero cell count

* handle seq rm return value

* unused param

* keep in the size check

* fix return types

* add server test case for slot save restore

* cleanup

* add cake

* cleanup style

* add special

* removing a whole sequence never fails

* move sequence state file functionality from server to llama to match session api and add version tags

* catch exceptions on save as well

* error log messages

* check types for stricter restore

* update server doc

* readme : update API changes date

* strict filename validation

* move include, reject bom as well

* also reject empty filename

* reject whitespace and trailing dot

---------

Co-authored-by: Martin Evans <martindevans@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---
 README.md                                     |   1 +
 common/common.cpp                             |  73 ++-
 common/common.h                               |   2 +
 examples/main/main.cpp                        |   6 +-
 examples/save-load-state/save-load-state.cpp  | 101 +++-
 examples/server/README.md                     |  52 ++
 examples/server/server.cpp                    | 228 ++++++++-
 .../server/tests/features/slotsave.feature    |  58 +++
 examples/server/tests/features/steps/steps.py |  60 +++
 llama.cpp                                     | 463 +++++++++++++++++-
 llama.h                                       |  73 ++-
 11 files changed, 1086 insertions(+), 31 deletions(-)
 create mode 100644 examples/server/tests/features/slotsave.feature

diff --git a/README.md b/README.md
index 6d9961120..a4897fc36 100644
--- a/README.md
+++ b/README.md
@@ -10,6 +10,7 @@ Inference of Meta's [LLaMA](https://arxiv.org/abs/2302.13971) model (and others)
 
 ### Recent API changes
 
+- [2024 Apr 4] State and session file functions reorganized under `llama_state_*` https://github.com/ggerganov/llama.cpp/pull/6341
 - [2024 Mar 26] Logits and embeddings API updated for compactness https://github.com/ggerganov/llama.cpp/pull/6122
 - [2024 Mar 13] Add `llama_synchronize()` + `llama_context_params.n_ubatch` https://github.com/ggerganov/llama.cpp/pull/6017
 - [2024 Mar 8] `llama_kv_cache_seq_rm()` returns a `bool` instead of `void`, and new `llama_n_seq_max()` returns the upper limit of acceptable `seq_id` in batches (relevant when dealing with multiple sequences) https://github.com/ggerganov/llama.cpp/pull/5328
diff --git a/common/common.cpp b/common/common.cpp
index 3e2df6e34..7d983a453 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -16,6 +16,7 @@
 #include <unordered_set>
 #include <vector>
 #include <cinttypes>
+#include <codecvt>
 
 #if defined(__APPLE__) && defined(__MACH__)
 #include <sys/types.h>
@@ -27,7 +28,6 @@
 #ifndef NOMINMAX
 #   define NOMINMAX
 #endif
-#include <codecvt>
 #include <locale>
 #include <windows.h>
 #include <fcntl.h>
@@ -1500,6 +1500,77 @@ std::string gpt_random_prompt(std::mt19937 & rng) {
     GGML_UNREACHABLE();
 }
 
+// Validate if a filename is safe to use
+// To validate a full path, split the path by the OS-specific path separator, and validate each part with this function
+bool validate_file_name(const std::string & filename) {
+    if (!filename.length()) {
+        // Empty filename invalid
+        return false;
+    }
+    if (filename.length() > 255) {
+        // Limit at common largest possible filename on Linux filesystems
+        // to avoid unnecessary further validation
+        // (On systems with smaller limits it will be caught by the OS)
+        return false;
+    }
+
+    std::u32string filename_utf32;
+    try {
+        std::wstring_convert<std::codecvt_utf8<char32_t>, char32_t> converter;
+        filename_utf32 = converter.from_bytes(filename);
+
+        // If the reverse conversion mismatches, it means overlong UTF-8 sequences were used,
+        // or invalid encodings were encountered. Reject such attempts
+        std::string filename_reencoded = converter.to_bytes(filename_utf32);
+        if (filename_reencoded != filename) {
+            return false;
+        }
+    } catch (const std::exception &) {
+        return false;
+    }
+
+    // Check for forbidden codepoints:
+    // - Control characters
+    // - Unicode equivalents of illegal characters
+    // - UTF-16 surrogate pairs
+    // - UTF-8 replacement character
+    // - Byte order mark (BOM)
+    // - Illegal characters: / \ : * ? " < > |
+    for (char32_t c : filename_utf32) {
+        if (c <= 0x1F // Control characters (C0)
+            || c == 0x7F // Control characters (DEL)
+            || (c >= 0x80 && c <= 0x9F) // Control characters (C1)
+            || c == 0xFF0E // Fullwidth Full Stop (period equivalent)
+            || c == 0x2215 // Division Slash (forward slash equivalent)
+            || c == 0x2216 // Set Minus (backslash equivalent)
+            || (c >= 0xD800 && c <= 0xDFFF) // UTF-16 surrogate pairs
+            || c == 0xFFFD // Replacement Character (UTF-8)
+            || c == 0xFEFF // Byte Order Mark (BOM)
+            || c == '/' || c == '\\' || c == ':' || c == '*' // Illegal characters
+            || c == '?' || c == '"' || c == '<' || c == '>' || c == '|') {
+            return false;
+        }
+    }
+
+    // Reject any leading or trailing ' ', or any trailing '.', these are stripped on Windows and will cause a different filename
+    // Unicode and other whitespace is not affected, only 0x20 space
+    if (filename.front() == ' ' || filename.back() == ' ' || filename.back() == '.') {
+        return false;
+    }
+
+    // Reject any ".." (currently stricter than necessary, it should be fine to just check for == ".." instead)
+    if (filename.find("..") != std::string::npos) {
+        return false;
+    }
+
+    // Reject "."
+    if (filename == ".") {
+        return false;
+    }
+
+    return true;
+}
+
 //
 // String utils
 //
diff --git a/common/common.h b/common/common.h
index 99ee90bc3..4635e05d6 100644
--- a/common/common.h
+++ b/common/common.h
@@ -179,6 +179,8 @@ std::string gpt_random_prompt(std::mt19937 & rng);
 
 void process_escapes(std::string& input);
 
+bool validate_file_name(const std::string & filename);
+
 //
 // String utils
 //
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index e2d07a631..711f162d7 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -235,7 +235,7 @@ int main(int argc, char ** argv) {
             // The file exists and is not empty
             session_tokens.resize(n_ctx);
             size_t n_token_count_out = 0;
-            if (!llama_load_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.capacity(), &n_token_count_out)) {
+            if (!llama_state_load_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.capacity(), &n_token_count_out)) {
                 LOG_TEE("%s: error: failed to load session file '%s'\n", __func__, path_session.c_str());
                 return 1;
             }
@@ -693,7 +693,7 @@ int main(int argc, char ** argv) {
             // optionally save the session on first sample (for faster prompt loading next time)
             if (!path_session.empty() && need_to_save_session && !params.prompt_cache_ro) {
                 need_to_save_session = false;
-                llama_save_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size());
+                llama_state_save_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size());
 
                 LOG("saved session to %s\n", path_session.c_str());
             }
@@ -935,7 +935,7 @@ int main(int argc, char ** argv) {
 
     if (!path_session.empty() && params.prompt_cache_all && !params.prompt_cache_ro) {
         LOG_TEE("\n%s: saving final output to session file '%s'\n", __func__, path_session.c_str());
-        llama_save_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size());
+        llama_state_save_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size());
     }
 
     llama_print_timings(ctx);
diff --git a/examples/save-load-state/save-load-state.cpp b/examples/save-load-state/save-load-state.cpp
index ef952e2bd..c3b766882 100644
--- a/examples/save-load-state/save-load-state.cpp
+++ b/examples/save-load-state/save-load-state.cpp
@@ -24,6 +24,7 @@ int main(int argc, char ** argv) {
 
     std::string result0;
     std::string result1;
+    std::string result2;
 
     // init
     llama_model * model;
@@ -44,8 +45,8 @@ int main(int argc, char ** argv) {
 
     // save state (rng, logits, embedding and kv_cache) to file
     {
-        std::vector<uint8_t> state_mem(llama_get_state_size(ctx));
-        const size_t written = llama_copy_state_data(ctx, state_mem.data());
+        std::vector<uint8_t> state_mem(llama_state_get_size(ctx));
+        const size_t written = llama_state_get_data(ctx, state_mem.data());
 
         FILE *fp_write = fopen("dump_state.bin", "wb");
         fwrite(state_mem.data(), 1, written, fp_write);
@@ -97,13 +98,13 @@ int main(int argc, char ** argv) {
 
     // load state (rng, logits, embedding and kv_cache) from file
     {
-        std::vector<uint8_t> state_mem(llama_get_state_size(ctx2));
+        std::vector<uint8_t> state_mem(llama_state_get_size(ctx2));
 
         FILE * fp_read = fopen("dump_state.bin", "rb");
         const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read);
         fclose(fp_read);
 
-        if (read != llama_set_state_data(ctx2, state_mem.data())) {
+        if (read != llama_state_set_data(ctx2, state_mem.data())) {
             fprintf(stderr, "\n%s : failed to read state\n", __func__);
             llama_free(ctx2);
             llama_free_model(model);
@@ -141,16 +142,104 @@ int main(int argc, char ** argv) {
         n_past += 1;
     }
 
-    printf("\n");
+    printf("\n\n");
 
     llama_free(ctx2);
-    llama_free_model(model);
 
     if (result0 != result1) {
         fprintf(stderr, "\n%s : error : the 2 generations are different\n", __func__);
         return 1;
     }
 
+    // make new context
+    auto* ctx3 = llama_new_context_with_model(model, llama_context_params_from_gpt_params(params));
+
+    printf("\nsingle seq run: %s", params.prompt.c_str());
+
+    // load state (rng, logits, embedding and kv_cache) from file
+    {
+        std::vector<uint8_t> state_mem(llama_state_get_size(ctx3));
+
+        FILE * fp_read = fopen("dump_state.bin", "rb");
+        const size_t read = fread(state_mem.data(), 1, state_mem.size(), fp_read);
+        fclose(fp_read);
+
+        if (read != llama_state_set_data(ctx3, state_mem.data())) {
+            fprintf(stderr, "\n%s : failed to read state\n", __func__);
+            llama_free(ctx3);
+            llama_free_model(model);
+            return 1;
+        }
+
+        fprintf(stderr, "%s : deserialized state from %zd out of a maximum of %zd bytes\n", __func__, read, state_mem.size());
+    }
+
+    // restore state (last tokens)
+    n_past = n_past_saved;
+
+    // save seq 0 and load into seq 1
+    {
+        // save kv of seq 0
+        std::vector<uint8_t> seq_store(llama_state_seq_get_size(ctx3, 0));
+        const size_t ncopy = llama_state_seq_get_data(ctx3, seq_store.data(), 0);
+        if (ncopy != seq_store.size()) {
+            fprintf(stderr, "\n%s : seq copy data length %zd does not match expected length %zd\n", __func__, ncopy, seq_store.size());
+            llama_free(ctx3);
+            llama_free_model(model);
+            return 1;
+        }
+        fprintf(stderr, "%s : seq 0 copied, %zd bytes\n", __func__, ncopy);
+
+        // erase whole kv
+        llama_kv_cache_clear(ctx3);
+        fprintf(stderr, "%s : kv cache cleared\n", __func__);
+
+        // restore kv into seq 1
+        const size_t nset = llama_state_seq_set_data(ctx3, seq_store.data(), 1);
+        if (nset != seq_store.size()) {
+            fprintf(stderr, "\n%s : seq set data length %zd does not match expected length %zd\n", __func__, nset, seq_store.size());
+            llama_free(ctx3);
+            llama_free_model(model);
+            return 1;
+        }
+        fprintf(stderr, "%s : seq 1 restored, %zd bytes\n", __func__, nset);
+    }
+
+    // third run with seq 1 instead of 0
+    for (auto i = 0; i < params.n_predict; i++) {
+        auto * logits = llama_get_logits(ctx3);
+        auto n_vocab = llama_n_vocab(model);
+        std::vector<llama_token_data> candidates;
+        candidates.reserve(n_vocab);
+        for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
+            candidates.emplace_back(llama_token_data{token_id, logits[token_id], 0.0f});
+        }
+        llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
+        auto next_token = llama_sample_token(ctx3, &candidates_p);
+        auto next_token_str = llama_token_to_piece(ctx3, next_token);
+
+        printf("%s", next_token_str.c_str());
+        result2 += next_token_str;
+
+        if (llama_decode(ctx3, llama_batch_get_one(&next_token, 1, n_past, 1))) {
+            fprintf(stderr, "\n%s : failed to evaluate\n", __func__);
+            llama_free(ctx3);
+            llama_free_model(model);
+            return 1;
+        }
+        n_past += 1;
+    }
+
+    printf("\n");
+
+    llama_free(ctx3);
+    llama_free_model(model);
+
+    if (result0 != result2) {
+        fprintf(stderr, "\n%s : error : the seq restore generation is different\n", __func__);
+        return 1;
+    }
+
     fprintf(stderr, "\n%s : success\n", __func__);
 
     return 0;
diff --git a/examples/server/README.md b/examples/server/README.md
index 0d8564a1f..a6fc92eaa 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -57,6 +57,7 @@ page cache before using this. See https://github.com/ggerganov/llama.cpp/issues/
 - `-n N, --n-predict N`: Set the maximum tokens to predict. Default: `-1`
 - `--slots-endpoint-disable`: To disable slots state monitoring endpoint. Slots state may contain user data, prompts included.
 - `--metrics`: enable prometheus `/metrics` compatible endpoint. Default: disabled
+- `--slot-save-path PATH`: Specifies the path where the state of slots (the prompt cache) can be stored. If not provided, the slot management endpoints will be disabled.
 - `--chat-template JINJA_TEMPLATE`: Set custom jinja chat template. This parameter accepts a string, not a file name.  Default: template taken from model's metadata. We only support [some pre-defined templates](https://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template)
 - `--log-disable`: Output logs to stdout only, not to `llama.log`. Default: enabled
 - `--log-format FORMAT`: Define the log output to FORMAT: json or text Default: `json`
@@ -517,6 +518,57 @@ Available metrics:
 - `llamacpp:requests_processing`: Number of requests processing.
 - `llamacpp:requests_deferred`: Number of requests deferred.
 
+- **POST** `/slots/{id_slot}?action=save`: Save the prompt cache of the specified slot to a file.
+
+    *Options:*
+
+    `filename`: Name of the file to save the slot's prompt cache. The file will be saved in the directory specified by the `--slot-save-path` server parameter.
+
+### Result JSON
+
+```json
+{
+    "id_slot": 0,
+    "filename": "slot_save_file.bin",
+    "n_saved": 1745,
+    "n_written": 14309796,
+    "timings": {
+        "save_ms": 49.865
+    }
+}
+```
+
+- **POST** `/slots/{id_slot}?action=restore`: Restore the prompt cache of the specified slot from a file.
+
+    *Options:*
+
+    `filename`: Name of the file to restore the slot's prompt cache from. The file should be located in the directory specified by the `--slot-save-path` server parameter.
+
+### Result JSON
+
+```json
+{
+    "id_slot": 0,
+    "filename": "slot_save_file.bin",
+    "n_restored": 1745,
+    "n_read": 14309796,
+    "timings": {
+        "restore_ms": 42.937
+    }
+}
+```
+
+- **POST** `/slots/{id_slot}?action=erase`: Erase the prompt cache of the specified slot.
+
+### Result JSON
+
+```json
+{
+    "id_slot": 0,
+    "n_erased": 1745
+}
+```
+
 ## More examples
 
 ### Change system prompt on runtime
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 183f0d3c8..6c64fe3e1 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -61,7 +61,10 @@ enum server_task_type {
     SERVER_TASK_TYPE_COMPLETION,
     SERVER_TASK_TYPE_CANCEL,
     SERVER_TASK_TYPE_NEXT_RESPONSE,
-    SERVER_TASK_TYPE_METRICS
+    SERVER_TASK_TYPE_METRICS,
+    SERVER_TASK_TYPE_SLOT_SAVE,
+    SERVER_TASK_TYPE_SLOT_RESTORE,
+    SERVER_TASK_TYPE_SLOT_ERASE,
 };
 
 struct server_task {
@@ -128,6 +131,7 @@ struct server_params {
 
     bool slots_endpoint   = true;
     bool metrics_endpoint = false;
+    std::string slot_save_path;
 };
 
 struct server_slot {
@@ -1612,6 +1616,107 @@ struct server_context {
                     }
                     queue_results.send(res);
                 } break;
+            case SERVER_TASK_TYPE_SLOT_SAVE:
+                {
+                    int id_slot = task.data["id_slot"];
+                    server_slot * slot = get_slot(id_slot);
+                    if (slot == nullptr) {
+                        send_error(task, "Invalid slot ID", ERROR_TYPE_INVALID_REQUEST);
+                        break;
+                    }
+
+                    const size_t token_count = slot->cache_tokens.size();
+                    const int64_t t_start = ggml_time_us();
+
+                    std::string filename = task.data["filename"];
+                    std::string filepath = task.data["filepath"];
+
+                    const size_t nwrite = llama_state_seq_save_file(ctx, filepath.c_str(), slot->id + 1, slot->cache_tokens.data(), token_count);
+
+                    const int64_t t_end = ggml_time_us();
+                    const double t_save_ms = (t_end - t_start) / 1000.0;
+
+                    server_task_result result;
+                    result.id = task.id;
+                    result.stop = true;
+                    result.error = false;
+                    result.data = json {
+                        { "id_slot",   id_slot },
+                        { "filename",  filename },
+                        { "n_saved",   token_count }, // tokens saved
+                        { "n_written", nwrite },      // bytes written
+                        { "timings", {
+                            { "save_ms", t_save_ms }
+                        } }
+                    };
+                    queue_results.send(result);
+                } break;
+            case SERVER_TASK_TYPE_SLOT_RESTORE:
+                {
+                    int id_slot = task.data["id_slot"];
+                    server_slot * slot = get_slot(id_slot);
+                    if (slot == nullptr) {
+                        send_error(task, "Invalid slot ID", ERROR_TYPE_INVALID_REQUEST);
+                        break;
+                    }
+
+                    const int64_t t_start = ggml_time_us();
+
+                    std::string filename = task.data["filename"];
+                    std::string filepath = task.data["filepath"];
+
+                    slot->cache_tokens.resize(slot->n_ctx);
+                    size_t token_count = 0;
+                    size_t nread = llama_state_seq_load_file(ctx, filepath.c_str(), slot->id + 1, slot->cache_tokens.data(), slot->cache_tokens.size(), &token_count);
+                    if (nread == 0) {
+                        slot->cache_tokens.resize(0);
+                        send_error(task, "Unable to restore slot, no available space in KV cache or invalid slot save file", ERROR_TYPE_INVALID_REQUEST);
+                        break;
+                    }
+                    slot->cache_tokens.resize(token_count);
+
+                    const int64_t t_end = ggml_time_us();
+                    const double t_restore_ms = (t_end - t_start) / 1000.0;
+
+                    server_task_result result;
+                    result.id = task.id;
+                    result.stop = true;
+                    result.error = false;
+                    result.data = json {
+                        { "id_slot",    id_slot },
+                        { "filename",   filename },
+                        { "n_restored", token_count }, // tokens restored
+                        { "n_read",     nread },       // bytes read
+                        { "timings", {
+                            { "restore_ms", t_restore_ms }
+                        } }
+                    };
+                    queue_results.send(result);
+                } break;
+            case SERVER_TASK_TYPE_SLOT_ERASE:
+                {
+                    int id_slot = task.data["id_slot"];
+                    server_slot * slot = get_slot(id_slot);
+                    if (slot == nullptr) {
+                        send_error(task, "Invalid slot ID", ERROR_TYPE_INVALID_REQUEST);
+                        break;
+                    }
+
+                    // Erase token cache
+                    const size_t n_erased = slot->cache_tokens.size();
+                    llama_kv_cache_seq_rm(ctx, slot->id + 1, -1, -1);
+                    slot->cache_tokens.clear();
+
+                    server_task_result result;
+                    result.id = task.id;
+                    result.stop = true;
+                    result.error = false;
+                    result.data = json {
+                        { "id_slot",  id_slot },
+                        { "n_erased", n_erased }
+                    };
+                    queue_results.send(result);
+                } break;
         }
     }
 
@@ -2249,6 +2354,7 @@ static void server_print_usage(const char * argv0, const gpt_params & params, co
     printf("  --log-disable             disables logging to a file.\n");
     printf("  --slots-endpoint-disable  disables slots monitoring endpoint.\n");
     printf("  --metrics                 enable prometheus compatible metrics endpoint (default: %s).\n", sparams.metrics_endpoint ? "enabled" : "disabled");
+    printf("  --slot-save-path PATH     path to save slot kv cache (default: disabled)\n");
     printf("\n");
     printf("  -n, --n-predict           maximum tokens to predict (default: %d)\n", params.n_predict);
     printf("  --override-kv KEY=TYPE:VALUE\n");
@@ -2657,6 +2763,16 @@ static void server_params_parse(int argc, char ** argv, server_params & sparams,
             sparams.slots_endpoint = false;
         } else if (arg == "--metrics") {
             sparams.metrics_endpoint = true;
+        } else if (arg == "--slot-save-path") {
+            if (++i >= argc) {
+                invalid_param = true;
+                break;
+            }
+            sparams.slot_save_path = argv[i];
+            // if doesn't end with DIRECTORY_SEPARATOR, add it
+            if (!sparams.slot_save_path.empty() && sparams.slot_save_path[sparams.slot_save_path.size() - 1] != DIRECTORY_SEPARATOR) {
+                sparams.slot_save_path += DIRECTORY_SEPARATOR;
+            }
         } else if (arg == "--chat-template") {
             if (++i >= argc) {
                 invalid_param = true;
@@ -3159,6 +3275,112 @@ int main(int argc, char ** argv) {
         res.status = 200; // HTTP OK
     };
 
+    const auto handle_slots_save = [&ctx_server, &res_error, &sparams](const httplib::Request & req, httplib::Response & res, int id_slot) {
+        json request_data = json::parse(req.body);
+        std::string filename = request_data["filename"];
+        if (!validate_file_name(filename)) {
+            res_error(res, format_error_response("Invalid filename", ERROR_TYPE_INVALID_REQUEST));
+            return;
+        }
+        std::string filepath = sparams.slot_save_path + filename;
+
+        server_task task;
+        task.type = SERVER_TASK_TYPE_SLOT_SAVE;
+        task.data = {
+            { "id_slot", id_slot },
+            { "filename", filename },
+            { "filepath", filepath }
+        };
+
+        const int id_task = ctx_server.queue_tasks.post(task);
+        ctx_server.queue_results.add_waiting_task_id(id_task);
+
+        server_task_result result = ctx_server.queue_results.recv(id_task);
+        ctx_server.queue_results.remove_waiting_task_id(id_task);
+
+        if (result.error) {
+            res_error(res, result.data);
+        } else {
+            res.set_content(result.data.dump(), "application/json");
+        }
+    };
+
+    const auto handle_slots_restore = [&ctx_server, &res_error, &sparams](const httplib::Request & req, httplib::Response & res, int id_slot) {
+        json request_data = json::parse(req.body);
+        std::string filename = request_data["filename"];
+        if (!validate_file_name(filename)) {
+            res_error(res, format_error_response("Invalid filename", ERROR_TYPE_INVALID_REQUEST));
+            return;
+        }
+        std::string filepath = sparams.slot_save_path + filename;
+
+        server_task task;
+        task.type = SERVER_TASK_TYPE_SLOT_RESTORE;
+        task.data = {
+            { "id_slot", id_slot },
+            { "filename", filename },
+            { "filepath", filepath }
+        };
+
+        const int id_task = ctx_server.queue_tasks.post(task);
+        ctx_server.queue_results.add_waiting_task_id(id_task);
+
+        server_task_result result = ctx_server.queue_results.recv(id_task);
+        ctx_server.queue_results.remove_waiting_task_id(id_task);
+
+        if (result.error) {
+            res_error(res, result.data);
+        } else {
+            res.set_content(result.data.dump(), "application/json");
+        }
+    };
+
+    const auto handle_slots_erase = [&ctx_server, &res_error](const httplib::Request & /* req */, httplib::Response & res, int id_slot) {
+        server_task task;
+        task.type = SERVER_TASK_TYPE_SLOT_ERASE;
+        task.data = {
+            { "id_slot", id_slot },
+        };
+
+        const int id_task = ctx_server.queue_tasks.post(task);
+        ctx_server.queue_results.add_waiting_task_id(id_task);
+
+        server_task_result result = ctx_server.queue_results.recv(id_task);
+        ctx_server.queue_results.remove_waiting_task_id(id_task);
+
+        if (result.error) {
+            res_error(res, result.data);
+        } else {
+            res.set_content(result.data.dump(), "application/json");
+        }
+    };
+
+    const auto handle_slots_action = [&res_error, &handle_slots_save, &handle_slots_restore, &handle_slots_erase](const httplib::Request & req, httplib::Response & res) {
+        res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
+
+        std::string id_slot_str = req.path_params.at("id_slot");
+        int id_slot;
+
+        try {
+            id_slot = std::stoi(id_slot_str);
+        } catch (const std::exception &) {
+            res_error(res, format_error_response("Invalid slot ID", ERROR_TYPE_INVALID_REQUEST));
+            return;
+        }
+
+        std::string action = req.get_param_value("action");
+
+        if (action == "save") {
+            handle_slots_save(req, res, id_slot);
+        } else if (action == "restore") {
+            handle_slots_restore(req, res, id_slot);
+        } else if (action == "erase") {
+            handle_slots_erase(req, res, id_slot);
+        } else {
+            res_error(res, format_error_response("Invalid action", ERROR_TYPE_INVALID_REQUEST));
+        }
+    };
+
     const auto handle_props = [&ctx_server](const httplib::Request & req, httplib::Response & res) {
         res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
         json data = {
@@ -3521,6 +3743,10 @@ int main(int argc, char ** argv) {
     svr->Post("/v1/embeddings",       handle_embeddings);
     svr->Post("/tokenize",            handle_tokenize);
     svr->Post("/detokenize",          handle_detokenize);
+    if (!sparams.slot_save_path.empty()) {
+        // only enable slot endpoints if slot_save_path is set
+        svr->Post("/slots/:id_slot",  handle_slots_action);
+    }
 
     //
     // Start the server
diff --git a/examples/server/tests/features/slotsave.feature b/examples/server/tests/features/slotsave.feature
new file mode 100644
index 000000000..1c281c074
--- /dev/null
+++ b/examples/server/tests/features/slotsave.feature
@@ -0,0 +1,58 @@
+@llama.cpp
+@slotsave
+Feature: llama.cpp server slot management
+
+  Background: Server startup
+    Given a server listening on localhost:8080
+    And   a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models
+    And   prompt caching is enabled
+    And   2 slots
+    And   . as slot save path
+    And   2048 KV cache size
+    And   42 as server seed
+    And   24 max tokens to predict
+    Then  the server is starting
+    Then  the server is healthy
+
+  Scenario: Save and Restore Slot
+    # First prompt in slot 1 should be fully processed
+    Given a user prompt "What is the capital of France?"
+    And   using slot id 1
+    And   a completion request with no api error
+    Then  24 tokens are predicted matching (Lily|cake)
+    And   22 prompt tokens are processed
+    When  the slot 1 is saved with filename "slot1.bin"
+    Then  the server responds with status code 200
+    # Since we have cache, this should only process the last tokens
+    Given a user prompt "What is the capital of Germany?"
+    And   a completion request with no api error
+    Then  24 tokens are predicted matching (Thank|special)
+    And   7 prompt tokens are processed
+    # Loading the original cache into slot 0,
+    # we should only be processing 1 prompt token and get the same output
+    When  the slot 0 is restored with filename "slot1.bin"
+    Then  the server responds with status code 200
+    Given a user prompt "What is the capital of France?"
+    And   using slot id 0
+    And   a completion request with no api error
+    Then  24 tokens are predicted matching (Lily|cake)
+    And   1 prompt tokens are processed
+    # For verification that slot 1 was not corrupted during slot 0 load, same thing
+    Given a user prompt "What is the capital of Germany?"
+    And   using slot id 1
+    And   a completion request with no api error
+    Then  24 tokens are predicted matching (Thank|special)
+    And   1 prompt tokens are processed
+
+  Scenario: Erase Slot
+    Given a user prompt "What is the capital of France?"
+    And   using slot id 1
+    And   a completion request with no api error
+    Then  24 tokens are predicted matching (Lily|cake)
+    And   22 prompt tokens are processed
+    When  the slot 1 is erased
+    Then  the server responds with status code 200
+    Given a user prompt "What is the capital of France?"
+    And   a completion request with no api error
+    Then  24 tokens are predicted matching (Lily|cake)
+    And   22 prompt tokens are processed
diff --git a/examples/server/tests/features/steps/steps.py b/examples/server/tests/features/steps/steps.py
index 9a6cf7d6a..ca400efa4 100644
--- a/examples/server/tests/features/steps/steps.py
+++ b/examples/server/tests/features/steps/steps.py
@@ -49,6 +49,9 @@ def step_server_config(context, server_fqdn, server_port):
     context.n_predict = None
     context.n_prompts = 0
     context.n_server_predict = None
+    context.slot_save_path = None
+    context.id_slot = None
+    context.cache_prompt = None
     context.n_slots = None
     context.prompt_prefix = None
     context.prompt_suffix = None
@@ -119,6 +122,21 @@ def step_server_n_predict(context, n_predict):
     context.n_server_predict = n_predict
 
 
+@step('{slot_save_path} as slot save path')
+def step_slot_save_path(context, slot_save_path):
+    context.slot_save_path = slot_save_path
+
+
+@step('using slot id {id_slot:d}')
+def step_id_slot(context, id_slot):
+    context.id_slot = id_slot
+
+
+@step('prompt caching is enabled')
+def step_enable_prompt_cache(context):
+    context.cache_prompt = True
+
+
 @step('continuous batching')
 def step_server_continuous_batching(context):
     context.server_continuous_batching = True
@@ -212,6 +230,8 @@ async def step_request_completion(context, api_error):
                                           context.base_url,
                                           debug=context.debug,
                                           n_predict=context.n_predict,
+                                          cache_prompt=context.cache_prompt,
+                                          id_slot=context.id_slot,
                                           seed=await completions_seed(context),
                                           expect_api_error=expect_api_error,
                                           user_api_key=context.user_api_key)
@@ -711,12 +731,48 @@ async def concurrent_requests(context, f_completion, *args, **kwargs):
     await asyncio.sleep(0.1)
 
 
+@step('the slot {slot_id:d} is saved with filename "{filename}"')
+@async_run_until_complete
+async def step_save_slot(context, slot_id, filename):
+    async with aiohttp.ClientSession() as session:
+        async with session.post(f'{context.base_url}/slots/{slot_id}?action=save',
+                                json={"filename": filename},
+                                headers={"Content-Type": "application/json"}) as response:
+            context.response = response
+
+
+@step('the slot {slot_id:d} is restored with filename "{filename}"')
+@async_run_until_complete
+async def step_restore_slot(context, slot_id, filename):
+    async with aiohttp.ClientSession() as session:
+        async with session.post(f'{context.base_url}/slots/{slot_id}?action=restore',
+                                json={"filename": filename},
+                                headers={"Content-Type": "application/json"}) as response:
+            context.response = response
+
+
+@step('the slot {slot_id:d} is erased')
+@async_run_until_complete
+async def step_erase_slot(context, slot_id):
+    async with aiohttp.ClientSession() as session:
+        async with session.post(f'{context.base_url}/slots/{slot_id}?action=erase',
+                                headers={"Content-Type": "application/json"}) as response:
+            context.response = response
+
+
+@step('the server responds with status code {status_code:d}')
+def step_server_responds_with_status_code(context, status_code):
+    assert context.response.status == status_code
+
+
 async def request_completion(prompt,
                              base_url,
                              debug=False,
                              prompt_prefix=None,
                              prompt_suffix=None,
                              n_predict=None,
+                             cache_prompt=False,
+                             id_slot=None,
                              seed=None,
                              expect_api_error=None,
                              user_api_key=None):
@@ -738,6 +794,8 @@ async def request_completion(prompt,
                                     "prompt": prompt,
                                     "input_suffix": prompt_suffix,
                                     "n_predict": n_predict if n_predict is not None else -1,
+                                    "cache_prompt": cache_prompt,
+                                    "id_slot": id_slot,
                                     "seed": seed if seed is not None else 42
                                 },
                                 headers=headers,
@@ -1104,6 +1162,8 @@ def start_server_background(context):
         server_args.extend(['--parallel', context.n_slots])
     if context.n_server_predict:
         server_args.extend(['--n-predict', context.n_server_predict])
+    if context.slot_save_path:
+        server_args.extend(['--slot-save-path', context.slot_save_path])
     if context.server_api_key:
         server_args.extend(['--api-key', context.server_api_key])
     if context.n_ga:
diff --git a/llama.cpp b/llama.cpp
index 217726184..96d75518f 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -14907,9 +14907,33 @@ void llama_kv_cache_update(struct llama_context * ctx) {
     llama_kv_cache_update_internal(*ctx);
 }
 
+// deprecated
+size_t llama_get_state_size(const struct llama_context * ctx) {
+    return llama_state_get_size(ctx);
+}
+
+// deprecated
+size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dst) {
+    return llama_state_get_data(ctx, dst);
+}
+
+// deprecated
+size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {
+    return llama_state_set_data(ctx, src);
+}
+
+// deprecated
+bool llama_load_session_file(struct llama_context * ctx, const char * path_session, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
+    return llama_state_load_file(ctx, path_session, tokens_out, n_token_capacity, n_token_count_out);
+}
+
+// deprecated
+bool llama_save_session_file(struct llama_context * ctx, const char * path_session, const llama_token * tokens, size_t n_token_count) {
+    return llama_state_save_file(ctx, path_session, tokens, n_token_count);
+}
 
 // Returns the *maximum* size of the state
-size_t llama_get_state_size(const struct llama_context * ctx) {
+size_t llama_state_get_size(const struct llama_context * ctx) {
     const auto & cparams = ctx->cparams;
     const auto & hparams = ctx->model.hparams;
 
@@ -14997,15 +15021,15 @@ struct llama_data_file_context : llama_data_context {
  * file context:
  * llama_file file("/path", "wb");
  * llama_data_file_context data_ctx(&file);
- * llama_copy_state_data(ctx, &data_ctx);
+ * llama_state_get_data(ctx, &data_ctx);
  *
  * buffer context:
  * std::vector<uint8_t> buf(max_size, 0);
  * llama_data_buffer_context data_ctx(&buf.data());
- * llama_copy_state_data(ctx, &data_ctx);
+ * llama_state_get_data(ctx, &data_ctx);
  *
 */
-static void llama_copy_state_data_internal(struct llama_context * ctx, llama_data_context * data_ctx) {
+static void llama_state_get_data_internal(struct llama_context * ctx, llama_data_context * data_ctx) {
     // copy rng
     {
         std::ostringstream rng_ss;
@@ -15149,15 +15173,15 @@ static void llama_copy_state_data_internal(struct llama_context * ctx, llama_dat
     }
 }
 
-size_t llama_copy_state_data(struct llama_context * ctx, uint8_t * dst) {
+size_t llama_state_get_data(struct llama_context * ctx, uint8_t * dst) {
     llama_data_buffer_context data_ctx(dst);
-    llama_copy_state_data_internal(ctx, &data_ctx);
+    llama_state_get_data_internal(ctx, &data_ctx);
 
     return data_ctx.get_size_written();
 }
 
 // Sets the state reading from the specified source address
-size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {
+size_t llama_state_set_data(struct llama_context * ctx, const uint8_t * src) {
     const uint8_t * inp = src;
 
     // set rng
@@ -15309,14 +15333,14 @@ size_t llama_set_state_data(struct llama_context * ctx, const uint8_t * src) {
     }
 
     const size_t nread    = inp - src;
-    const size_t max_size = llama_get_state_size(ctx);
+    const size_t max_size = llama_state_get_size(ctx);
 
     GGML_ASSERT(nread <= max_size);
 
     return nread;
 }
 
-static bool llama_load_session_file_internal(struct llama_context * ctx, const char * path_session, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
+static bool llama_state_load_file_internal(struct llama_context * ctx, const char * path_session, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
     llama_file file(path_session, "rb");
 
     // sanity checks
@@ -15354,7 +15378,7 @@ static bool llama_load_session_file_internal(struct llama_context * ctx, const c
     // restore the context state
     {
         const size_t n_state_size_cur = file.size - file.tell();
-        const size_t n_state_size_max = llama_get_state_size(ctx);
+        const size_t n_state_size_max = llama_state_get_size(ctx);
 
         if (n_state_size_cur > n_state_size_max) {
             LLAMA_LOG_ERROR("%s : the state size in session file is too big! max %zu, got %zu\n", __func__, n_state_size_max, n_state_size_cur);
@@ -15364,22 +15388,22 @@ static bool llama_load_session_file_internal(struct llama_context * ctx, const c
         std::vector<uint8_t> state_data(n_state_size_max);
         file.read_raw(state_data.data(), n_state_size_cur);
 
-        llama_set_state_data(ctx, state_data.data());
+        llama_state_set_data(ctx, state_data.data());
     }
 
     return true;
 }
 
-bool llama_load_session_file(struct llama_context * ctx, const char * path_session, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
+bool llama_state_load_file(struct llama_context * ctx, const char * path_session, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
     try {
-        return llama_load_session_file_internal(ctx, path_session, tokens_out, n_token_capacity, n_token_count_out);
+        return llama_state_load_file_internal(ctx, path_session, tokens_out, n_token_capacity, n_token_count_out);
     } catch (const std::exception & err) {
         LLAMA_LOG_ERROR("error loading session file: %s\n", err.what());
         return false;
     }
 }
 
-bool llama_save_session_file(struct llama_context * ctx, const char * path_session, const llama_token * tokens, size_t n_token_count) {
+static bool llama_state_save_file_internal(struct llama_context * ctx, const char * path_session, const llama_token * tokens, size_t n_token_count) {
     llama_file file(path_session, "wb");
 
     file.write_u32(LLAMA_SESSION_MAGIC);
@@ -15393,11 +15417,420 @@ bool llama_save_session_file(struct llama_context * ctx, const char * path_sessi
 
     // save the context state using stream saving
     llama_data_file_context data_ctx(&file);
-    llama_copy_state_data_internal(ctx, &data_ctx);
+    llama_state_get_data_internal(ctx, &data_ctx);
 
     return true;
 }
 
+bool llama_state_save_file(struct llama_context * ctx, const char * path_session, const llama_token * tokens, size_t n_token_count) {
+    try {
+        return llama_state_save_file_internal(ctx, path_session, tokens, n_token_count);
+    } catch (const std::exception & err) {
+        LLAMA_LOG_ERROR("error saving session file: %s\n", err.what());
+        return false;
+    }
+}
+
+size_t llama_state_seq_get_size(struct llama_context* ctx, llama_seq_id seq_id) {
+    // save the size of size_t as a uint32_t for safety check
+    const size_t size_t_size_size = sizeof(uint32_t);
+
+    // other values
+    const size_t s_cell_count_size = sizeof(uint32_t);
+    const size_t s_layer_count_size = sizeof(uint32_t);
+    const size_t n_embd_v_gqa_size = sizeof(uint32_t);
+
+    size_t s_cell_count = 0;
+    size_t s_cell_data_size = 0;
+    const auto & kv_self = ctx->kv_self;
+    const auto & hparams = ctx->model.hparams;
+
+    const uint32_t n_layer = hparams.n_layer;
+    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
+    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
+
+    for (uint32_t i = 0; i < kv_self.size; ++i) {
+        const auto & cell = kv_self.cells[i];
+        if (cell.seq_id.count(seq_id) > 0) {
+            ++s_cell_count;
+            s_cell_data_size += sizeof(llama_pos);
+        }
+    }
+
+    for (int il = 0; il < (int)n_layer; ++il) {
+        // types of keys and values
+        s_cell_data_size += sizeof(int32_t) * 2;
+        // k_size_row and v_size_el values of layer
+        s_cell_data_size += sizeof(size_t) * 2;
+
+        // keys
+        const size_t k_size_row = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa);
+        s_cell_data_size += k_size_row * s_cell_count;
+
+        // values (transposed)
+        const size_t v_size_el = ggml_type_size(kv_self.v_l[il]->type);
+        s_cell_data_size += v_size_el * s_cell_count * n_embd_v_gqa;
+    }
+
+    const size_t s_total = (
+        size_t_size_size +
+        s_cell_count_size +
+        s_layer_count_size +
+        n_embd_v_gqa_size +
+        s_cell_data_size
+        );
+
+    return s_total;
+}
+
+static size_t llama_state_seq_get_data_internal(struct llama_context * ctx, llama_data_context & data_ctx, llama_seq_id seq_id) {
+    const auto & kv_self = ctx->kv_self;
+    GGML_ASSERT(!kv_self.recurrent); // not implemented
+
+    // Save the size of size_t as a uint32_t for safety check
+    const uint32_t size_t_size = sizeof(size_t);
+    data_ctx.write(&size_t_size, sizeof(size_t_size));
+
+    std::vector<std::pair<uint32_t, uint32_t>> cell_ranges; // ranges, from inclusive, to exclusive
+    uint32_t cell_count = 0;
+
+    // Count the number of cells with the specified seq_id
+    // Find all the ranges of cells with this seq id
+    {
+        uint32_t cell_range_begin = kv_self.size;
+        for (uint32_t i = 0; i < kv_self.size; ++i) {
+            const auto & cell = kv_self.cells[i];
+            if (cell.has_seq_id(seq_id)) {
+                ++cell_count;
+                if (cell_range_begin == kv_self.size) {
+                    cell_range_begin = i;
+                }
+            }
+            else {
+                if (cell_range_begin != kv_self.size) {
+                    cell_ranges.push_back({ cell_range_begin, i });
+                    cell_range_begin = kv_self.size;
+                }
+            }
+        }
+        if (cell_range_begin != kv_self.size) {
+            cell_ranges.push_back({ cell_range_begin, kv_self.size });
+        }
+
+        // DEBUG CHECK: Sum of cell counts in ranges should equal the total cell count
+        uint32_t cell_count_check = 0;
+        for (const auto & range : cell_ranges) {
+            cell_count_check += range.second - range.first;
+        }
+        GGML_ASSERT(cell_count == cell_count_check);
+    }
+
+    // Write the cell count
+    data_ctx.write(&cell_count, sizeof(cell_count));
+
+    const auto & hparams = ctx->model.hparams;
+    const uint32_t n_layer = hparams.n_layer;
+    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
+    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
+
+    // Write the layer count
+    data_ctx.write(&n_layer, sizeof(n_layer));
+
+    // Write n_embd_v_gqa
+    data_ctx.write(&n_embd_v_gqa, sizeof(n_embd_v_gqa));
+
+    // Iterate the ranges and write all the pos (this is the token position in the prompt)
+    for (const auto & range : cell_ranges) {
+        for (uint32_t i = range.first; i < range.second; ++i) {
+            const auto & cell = kv_self.cells[i];
+            data_ctx.write(&cell.pos, sizeof(cell.pos));
+        }
+    }
+
+    // Iterate and write all the keys first, each row is a cell
+    // Get whole range at a time
+    std::vector<uint8_t> tmp_buf;
+    for (int il = 0; il < (int)n_layer; ++il) {
+        // Write key type
+        const int32_t k_type_i = (int32_t)kv_self.k_l[il]->type;
+        data_ctx.write(&k_type_i, sizeof(k_type_i));
+
+        // Write row size of key
+        const size_t k_size_row = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa);
+        data_ctx.write(&k_size_row, sizeof(k_size_row));
+
+        // Read each range of cells of k_size length each into tmp_buf and write out
+        for (const auto & range : cell_ranges) {
+            const size_t range_size = range.second - range.first;
+            tmp_buf.resize(range_size * k_size_row);
+            ggml_backend_tensor_get(kv_self.k_l[il], tmp_buf.data(), range.first * k_size_row, range_size * k_size_row);
+            data_ctx.write(tmp_buf.data(), tmp_buf.size());
+        }
+    }
+
+    // For the values, they are transposed, so we also need the element size and get the element ranges from each row
+    const uint32_t kv_size = kv_self.size;
+    for (int il = 0; il < (int)n_layer; ++il) {
+        // Write value type
+        const int32_t v_type_i = (int32_t)kv_self.v_l[il]->type;
+        data_ctx.write(&v_type_i, sizeof(v_type_i));
+
+        // Write element size
+        const size_t v_size_el = ggml_type_size(kv_self.v_l[il]->type);
+        data_ctx.write(&v_size_el, sizeof(v_size_el));
+
+        // For each row, we get the element values of each cell
+        for (uint32_t j = 0; j < n_embd_v_gqa; ++j) {
+            // Read each range of cells of v_size_el length each into tmp_buf and write out
+            for (const auto & range : cell_ranges) {
+                const size_t range_size = range.second - range.first;
+                const size_t src_offset = (range.first + j * kv_size) * v_size_el;
+                tmp_buf.resize(range_size * v_size_el);
+                ggml_backend_tensor_get(kv_self.v_l[il], tmp_buf.data(), src_offset, tmp_buf.size());
+                data_ctx.write(tmp_buf.data(), tmp_buf.size());
+            }
+        }
+    }
+
+    return data_ctx.get_size_written();
+}
+
+size_t llama_state_seq_get_data(struct llama_context* ctx, uint8_t* dst, llama_seq_id seq_id) {
+    llama_data_buffer_context data_ctx(dst);
+    return llama_state_seq_get_data_internal(ctx, data_ctx, seq_id);
+}
+
+size_t llama_state_seq_set_data(struct llama_context * ctx, const uint8_t * src, llama_seq_id dest_seq_id) {
+    auto & kv_self = ctx->kv_self;
+    GGML_ASSERT(!kv_self.recurrent); // not implemented
+
+    // Wipe the slot
+    llama_kv_cache_seq_rm(kv_self, dest_seq_id, -1, -1);
+
+    const uint8_t * inp = src;
+
+    // Read size of size_t
+    uint32_t size_t_size;
+    memcpy(&size_t_size, inp, sizeof(size_t_size));
+    inp += sizeof(size_t_size);
+    if (size_t_size != sizeof(size_t)) {
+        LLAMA_LOG_ERROR("%s: size_t size mismatch\n", __func__);
+        return 0;
+    }
+
+    // Read the cell count
+    uint32_t cell_count;
+    memcpy(&cell_count, inp, sizeof(cell_count));
+    inp += sizeof(cell_count);
+
+    // Read the layer count
+    uint32_t n_layer_ref;
+    memcpy(&n_layer_ref, inp, sizeof(n_layer_ref));
+    inp += sizeof(n_layer_ref);
+
+    // Read n_embd_v_gqa
+    uint32_t n_embd_v_gqa_ref;
+    memcpy(&n_embd_v_gqa_ref, inp, sizeof(n_embd_v_gqa_ref));
+    inp += sizeof(n_embd_v_gqa_ref);
+
+    // Sanity check model compatibility
+    const auto & hparams = ctx->model.hparams;
+    const uint32_t n_layer = hparams.n_layer;
+    const uint32_t n_embd_k_gqa = hparams.n_embd_k_gqa() + hparams.n_embd_k_s();
+    const uint32_t n_embd_v_gqa = hparams.n_embd_v_gqa() + hparams.n_embd_v_s();
+    if (n_layer != n_layer_ref) {
+        LLAMA_LOG_ERROR("%s: mismatched n_layer (%d != %d)\n", __func__, n_layer, n_layer_ref);
+        return 0;
+    }
+    if (n_embd_v_gqa != n_embd_v_gqa_ref) {
+        LLAMA_LOG_ERROR("%s: mismatched n_embd_v_gqa (%d != %d)\n", __func__, n_embd_v_gqa, n_embd_v_gqa_ref);
+        return 0;
+    }
+
+    // Allocate the new cells for the slot
+    if (cell_count) {
+        llama_batch batch = llama_batch_init(cell_count, 0, 1);
+        batch.n_tokens = cell_count;
+        for (uint32_t i = 0; i < cell_count; ++i) {
+            llama_pos pos;
+            memcpy(&pos, inp, sizeof(pos));
+            inp += sizeof(pos);
+
+            batch.pos[i] = pos;
+            batch.n_seq_id[i] = 1;
+            batch.seq_id[i][0] = dest_seq_id;
+        }
+        if (!llama_kv_cache_find_slot(kv_self, batch)) {
+            llama_batch_free(batch);
+            LLAMA_LOG_ERROR("%s: failed to find available cells in kv cache\n", __func__);
+            return 0;
+        }
+
+        // DEBUG CHECK: kv_self.head should be our first cell, kv_self.head + cell_count - 1 should be our last cell (verify seq_id and pos values)
+        // Assume that this is one contiguous block of cells
+        GGML_ASSERT(kv_self.head + cell_count <= kv_self.size);
+        GGML_ASSERT(kv_self.cells[kv_self.head].pos == batch.pos[0]);
+        GGML_ASSERT(kv_self.cells[kv_self.head + cell_count - 1].pos == batch.pos[cell_count - 1]);
+        GGML_ASSERT(kv_self.cells[kv_self.head].has_seq_id(dest_seq_id));
+        GGML_ASSERT(kv_self.cells[kv_self.head + cell_count - 1].has_seq_id(dest_seq_id));
+
+        // Cleanup
+        llama_batch_free(batch);
+    }
+
+    const uint32_t kv_size = kv_self.size;
+    const uint32_t kv_head = kv_self.head;
+
+    // For each layer, read the keys for each cell, one row is one cell, read as one contiguous blo
+    for (int il = 0; il < (int)n_layer; ++il) {
+        // Read type of key
+        int32_t k_type_i_ref;
+        memcpy(&k_type_i_ref, inp, sizeof(k_type_i_ref));
+        inp += sizeof(k_type_i_ref);
+        const int32_t k_type_i = (int32_t)kv_self.k_l[il]->type;
+        if (k_type_i != k_type_i_ref) {
+            llama_kv_cache_seq_rm(kv_self, dest_seq_id, -1, -1);
+            LLAMA_LOG_ERROR("%s: mismatched key type (%d != %d, layer %d)\n", __func__, k_type_i, k_type_i_ref, il);
+            return 0;
+        }
+
+        // Read row size of key
+        size_t k_size_row_ref;
+        memcpy(&k_size_row_ref, inp, sizeof(k_size_row_ref));
+        inp += sizeof(k_size_row_ref);
+        const size_t k_size_row = ggml_row_size(kv_self.k_l[il]->type, n_embd_k_gqa);
+        if (k_size_row != k_size_row_ref) {
+            llama_kv_cache_seq_rm(kv_self, dest_seq_id, -1, -1);
+            LLAMA_LOG_ERROR("%s: mismatched key row size (%zu != %zu, layer %d)\n", __func__, k_size_row, k_size_row_ref, il);
+            return 0;
+        }
+
+        if (cell_count) {
+            // Read and set the keys for the whole cell range
+            ggml_backend_tensor_set(kv_self.k_l[il], inp, kv_head * k_size_row, cell_count * k_size_row);
+            inp += cell_count * k_size_row;
+        }
+    }
+
+    // For each layer, read the values for each cell (transposed)
+    for (int il = 0; il < (int)n_layer; ++il) {
+        // Read type of value
+        int32_t v_type_i_ref;
+        memcpy(&v_type_i_ref, inp, sizeof(v_type_i_ref));
+        inp += sizeof(v_type_i_ref);
+        const int32_t v_type_i = (int32_t)kv_self.v_l[il]->type;
+        if (v_type_i != v_type_i_ref) {
+            llama_kv_cache_seq_rm(kv_self, dest_seq_id, -1, -1);
+            LLAMA_LOG_ERROR("%s: mismatched value type (%d != %d, layer %d)\n", __func__, v_type_i, v_type_i_ref, il);
+            return 0;
+        }
+
+        // Read element size of value
+        size_t v_size_el_ref;
+        memcpy(&v_size_el_ref, inp, sizeof(v_size_el_ref));
+        inp += sizeof(v_size_el_ref);
+        const size_t v_size_el = ggml_type_size(kv_self.v_l[il]->type);
+        if (v_size_el != v_size_el_ref) {
+            llama_kv_cache_seq_rm(kv_self, dest_seq_id, -1, -1);
+            LLAMA_LOG_ERROR("%s: mismatched value element size (%zu != %zu, layer %d)\n", __func__, v_size_el, v_size_el_ref, il);
+            return 0;
+        }
+
+        if (cell_count) {
+            // For each row in the transposed matrix, read the values for the whole cell range
+            for (uint32_t j = 0; j < n_embd_v_gqa; ++j) {
+                const size_t dst_offset = (kv_head + j * kv_size) * v_size_el;
+                ggml_backend_tensor_set(kv_self.v_l[il], inp, dst_offset, cell_count * v_size_el);
+                inp += cell_count * v_size_el;
+            }
+        }
+    }
+
+    const size_t nread = inp - src;
+    return nread;
+}
+
+static size_t llama_state_seq_save_file_internal(struct llama_context * ctx, const char * filepath, llama_seq_id seq_id, const llama_token * tokens, size_t n_token_count) {
+    llama_file file(filepath, "wb");
+
+    file.write_u32(LLAMA_STATE_SEQ_MAGIC);
+    file.write_u32(LLAMA_STATE_SEQ_VERSION);
+
+    // save the prompt
+    file.write_u32((uint32_t)n_token_count);
+    file.write_raw(tokens, sizeof(llama_token) * n_token_count);
+
+    // save the context state using stream saving
+    llama_data_file_context data_ctx(&file);
+    llama_state_seq_get_data_internal(ctx, data_ctx, seq_id);
+
+    const size_t res = file.tell();
+    GGML_ASSERT(res == sizeof(uint32_t) * 3 + sizeof(llama_token) * n_token_count + data_ctx.get_size_written());
+    return res;
+}
+
+static size_t llama_state_seq_load_file_internal(struct llama_context * ctx, const char * filepath, llama_seq_id dest_seq_id, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
+    llama_file file(filepath, "rb");
+
+    // version checks
+    {
+        const uint32_t magic   = file.read_u32();
+        const uint32_t version = file.read_u32();
+
+        if (magic != LLAMA_STATE_SEQ_MAGIC || version != LLAMA_STATE_SEQ_VERSION) {
+            LLAMA_LOG_ERROR("%s: unknown (magic, version) for sequence state file: %08x, %08x\n", __func__, magic, version);
+            return 0;
+        }
+    }
+
+    // load the prompt
+    {
+        const uint32_t n_token_count = file.read_u32();
+
+        if (n_token_count > n_token_capacity) {
+            LLAMA_LOG_ERROR("%s: token count in sequence state file exceeded capacity! %u > %zu\n", __func__, n_token_count, n_token_capacity);
+            return 0;
+        }
+
+        file.read_raw(tokens_out, sizeof(llama_token) * n_token_count);
+        *n_token_count_out = n_token_count;
+    }
+
+    // restore the context state
+    {
+        const size_t state_size = file.size - file.tell();
+        std::vector<uint8_t> state_data(state_size);
+        file.read_raw(state_data.data(), state_size);
+        const size_t nread = llama_state_seq_set_data(ctx, state_data.data(), dest_seq_id);
+        if (!nread) {
+            LLAMA_LOG_ERROR("%s: failed to restore sequence state\n", __func__);
+            return 0;
+        }
+        GGML_ASSERT(nread <= state_size);
+        GGML_ASSERT(nread + sizeof(uint32_t) * 3 + sizeof(llama_token) * *n_token_count_out == file.tell());
+    }
+
+    return file.tell();
+}
+
+size_t llama_state_seq_save_file(struct llama_context * ctx, const char * filepath, llama_seq_id seq_id, const llama_token * tokens, size_t n_token_count) {
+    try {
+        return llama_state_seq_save_file_internal(ctx, filepath, seq_id, tokens, n_token_count);
+    } catch (const std::exception & err) {
+        LLAMA_LOG_ERROR("error saving sequence state file: %s\n", err.what());
+        return 0;
+    }
+}
+
+size_t llama_state_seq_load_file(struct llama_context * ctx, const char * filepath, llama_seq_id dest_seq_id, llama_token * tokens_out, size_t n_token_capacity, size_t * n_token_count_out) {
+    try {
+        return llama_state_seq_load_file_internal(ctx, filepath, dest_seq_id, tokens_out, n_token_capacity, n_token_count_out);
+    } catch (const std::exception & err) {
+        LLAMA_LOG_ERROR("error loading sequence state file: %s\n", err.what());
+        return 0;
+    }
+}
+
 void llama_set_n_threads(struct llama_context * ctx, uint32_t n_threads, uint32_t n_threads_batch) {
     ctx->cparams.n_threads       = n_threads;
     ctx->cparams.n_threads_batch = n_threads_batch;
diff --git a/llama.h b/llama.h
index 036b32685..2250130e2 100644
--- a/llama.h
+++ b/llama.h
@@ -37,10 +37,14 @@
 
 #define LLAMA_FILE_MAGIC_GGLA 0x67676c61u // 'ggla'
 #define LLAMA_FILE_MAGIC_GGSN 0x6767736eu // 'ggsn'
+#define LLAMA_FILE_MAGIC_GGSQ 0x67677371u // 'ggsq'
 
 #define LLAMA_SESSION_MAGIC   LLAMA_FILE_MAGIC_GGSN
 #define LLAMA_SESSION_VERSION 5
 
+#define LLAMA_STATE_SEQ_MAGIC   LLAMA_FILE_MAGIC_GGSQ
+#define LLAMA_STATE_SEQ_VERSION 1
+
 #ifdef __cplusplus
 extern "C" {
 #endif
@@ -523,6 +527,7 @@ extern "C" {
             struct llama_context * ctx);
 
     // Removes all tokens that belong to the specified sequence and have positions in [p0, p1)
+    // Returns false if a partial sequence cannot be removed. Removing a whole sequence never fails
     // seq_id < 0 : match any sequence
     // p0 < 0     : [0,  p1]
     // p1 < 0     : [p0, inf)
@@ -594,34 +599,92 @@ extern "C" {
 
     // Returns the maximum size in bytes of the state (rng, logits, embedding
     // and kv_cache) - will often be smaller after compacting tokens
-    LLAMA_API size_t llama_get_state_size(const struct llama_context * ctx);
+    LLAMA_API size_t llama_state_get_size(const struct llama_context * ctx);
+    LLAMA_API DEPRECATED(size_t llama_get_state_size(const struct llama_context * ctx),
+        "use llama_state_get_size instead");
 
     // Copies the state to the specified destination address.
     // Destination needs to have allocated enough memory.
     // Returns the number of bytes copied
-    LLAMA_API size_t llama_copy_state_data(
+    LLAMA_API size_t llama_state_get_data(
             struct llama_context * ctx,
                          uint8_t * dst);
+    LLAMA_API DEPRECATED(size_t llama_copy_state_data(
+            struct llama_context * ctx,
+                         uint8_t * dst),
+        "use llama_state_get_data instead");
 
     // Set the state reading from the specified address
     // Returns the number of bytes read
-    LLAMA_API size_t llama_set_state_data(
+    LLAMA_API size_t llama_state_set_data(
             struct llama_context * ctx,
                    const uint8_t * src);
+    LLAMA_API DEPRECATED(size_t llama_set_state_data(
+            struct llama_context * ctx,
+                   const uint8_t * src),
+        "use llama_state_set_data instead");
 
     // Save/load session file
-    LLAMA_API bool llama_load_session_file(
+    LLAMA_API bool llama_state_load_file(
             struct llama_context * ctx,
                       const char * path_session,
                      llama_token * tokens_out,
                           size_t   n_token_capacity,
                           size_t * n_token_count_out);
+    LLAMA_API DEPRECATED(bool llama_load_session_file(
+            struct llama_context * ctx,
+                      const char * path_session,
+                     llama_token * tokens_out,
+                          size_t   n_token_capacity,
+                          size_t * n_token_count_out),
+        "use llama_state_load_file instead");
 
-    LLAMA_API bool llama_save_session_file(
+    LLAMA_API bool llama_state_save_file(
             struct llama_context * ctx,
                       const char * path_session,
                const llama_token * tokens,
                           size_t   n_token_count);
+    LLAMA_API DEPRECATED(bool llama_save_session_file(
+            struct llama_context * ctx,
+                      const char * path_session,
+               const llama_token * tokens,
+                          size_t   n_token_count),
+        "use llama_state_save_file instead");
+
+    // Get the exact size needed to copy the KV cache of a single sequence
+    LLAMA_API size_t llama_state_seq_get_size(
+            struct llama_context * ctx,
+                    llama_seq_id   seq_id);
+
+    // Copy the KV cache of a single sequence into the specified buffer
+    LLAMA_API size_t llama_state_seq_get_data(
+            struct llama_context * ctx,
+                         uint8_t * dst,
+                    llama_seq_id   seq_id);
+
+    // Copy the sequence data (originally copied with `llama_state_seq_get_data`) into the specified sequence
+    // Returns:
+    //  - Positive: Ok
+    //  - Zero: Failed to load
+    LLAMA_API size_t llama_state_seq_set_data(
+            struct llama_context * ctx,
+                   const uint8_t * src,
+                    llama_seq_id   dest_seq_id);
+
+    LLAMA_API size_t llama_state_seq_save_file(
+            struct llama_context * ctx,
+                      const char * filepath,
+                    llama_seq_id   seq_id,
+               const llama_token * tokens,
+                          size_t   n_token_count);
+
+    LLAMA_API size_t llama_state_seq_load_file(
+            struct llama_context * ctx,
+                      const char * filepath,
+                    llama_seq_id   dest_seq_id,
+                     llama_token * tokens_out,
+                          size_t   n_token_capacity,
+                          size_t * n_token_count_out);
 
     //
     // Decoding

From e3c337d87ca650972105a51c6ce302dd236c07ad Mon Sep 17 00:00:00 2001
From: Rick G <26732651+TheFlipbook@users.noreply.github.com>
Date: Mon, 8 Apr 2024 06:02:30 -0700
Subject: [PATCH 3/9] llama : support negative ith in llama_get_ API (#6519)

* llama_sampling_sample with default args is more naively usable

* Batches populated by either llama_batch_get_one or llama_batch_add work with default args
  * Previously get_one could use the default argument
  * Previously add should usually have used the last index where logits[idx] == true
* This hopefully encourages the use of llama_batch_add
  * By giving expected results when using default arguments.
* Adds "negative indexing" feature to llama_get_logits_ith and llama_get_embeddings_ith
* Believed to work with any currently well behaved program
  * Default arg now works for both cases (previously would give strange results for add case)
  * Any non-negative number is unaffected and behaves as previously
  * Negative arguments were previously invalid.
* Implemented as a special case of indexing as suggested by @compilade in https://github.com/ggerganov/llama.cpp/pull/6519

* Fixed mismatch type errors

* cited in macOS CI tests
* Missed in original updates based on PR feedback in https://github.com/ggerganov/llama.cpp/pull/6519
---
 common/sampling.h |  2 +-
 llama.cpp         | 38 +++++++++++++++++++++++++++++---------
 llama.h           |  6 ++++--
 3 files changed, 34 insertions(+), 12 deletions(-)

diff --git a/common/sampling.h b/common/sampling.h
index 56ed991b8..639b819ab 100644
--- a/common/sampling.h
+++ b/common/sampling.h
@@ -129,7 +129,7 @@ llama_token llama_sampling_sample(
         struct llama_sampling_context * ctx_sampling,
         struct llama_context * ctx_main,
         struct llama_context * ctx_cfg,
-        int idx = 0);
+        int idx = -1);
 
 // Prepares and adjusts the set of token candidates for sampling based on penalties, biases, and sampling parameters.
 llama_token_data_array llama_sampling_prepare(
diff --git a/llama.cpp b/llama.cpp
index 96d75518f..9dde3efd0 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -2177,7 +2177,7 @@ struct llama_context {
 
     std::vector<int32_t> output_ids; // map batch token positions to ids of the logits and embd buffers
     size_t  output_size = 0; // capacity (of tokens positions) for the output buffers
-    int32_t n_outputs   = 0; // number of actually-used outputs in the current ubatch
+    int32_t n_outputs   = 0; // number of actually-used outputs in the current ubatch or last logical batch
 
     bool logits_all = false;
 
@@ -10411,6 +10411,9 @@ static int llama_decode_internal(
         n_outputs_prev += lctx.n_outputs;
     }
 
+    // set to total number of outputs in the batch, for use in llama_get_logits_ith
+    lctx.n_outputs = n_outputs;
+
     // wait for the computation to finish (automatically done when obtaining the model output)
     //llama_synchronize(&lctx);
 
@@ -15944,23 +15947,31 @@ float * llama_get_logits(struct llama_context * ctx) {
 }
 
 float * llama_get_logits_ith(struct llama_context * ctx, int32_t i) {
+    int32_t j = -1;
     llama_synchronize(ctx);
 
     try {
         if (ctx->logits == nullptr) {
             throw std::runtime_error("no logits");
         }
-        if ((size_t) i >= ctx->output_ids.size()) {
+
+        if (i < 0) {
+            j = ctx->n_outputs + i;
+            if (j < 0) {
+                throw std::runtime_error(format("negative index out of range [0, %d)", ctx->n_outputs));
+            }
+        } else if ((size_t) i >= ctx->output_ids.size()) {
             throw std::runtime_error(format("out of range [0, %lu)", ctx->output_ids.size()));
+        } else {
+            j = ctx->output_ids[i];
         }
-        const int32_t j = ctx->output_ids[i];
 
         if (j < 0) {
             throw std::runtime_error(format("batch.logits[%d] != true", i));
         }
-        if ((size_t) j >= ctx->output_size) {
+        if (j >= ctx->n_outputs) {
             // This should not happen
-            throw std::runtime_error(format("corrupt output buffer (j=%d, output_size=%lu)", j, ctx->output_size));
+            throw std::runtime_error(format("corrupt output buffer (j=%d, n_outputs=%d)", j, ctx->n_outputs));
         }
 
         return ctx->logits + j*ctx->model.hparams.n_vocab;
@@ -15980,23 +15991,32 @@ float * llama_get_embeddings(struct llama_context * ctx) {
 }
 
 float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i) {
+    int32_t j = -1;
+
     llama_synchronize(ctx);
 
     try {
         if (ctx->embd == nullptr) {
             throw std::runtime_error("no embeddings");
         }
-        if ((size_t) i >= ctx->output_ids.size()) {
+
+        if (i < 0) {
+            j = ctx->n_outputs + i;
+            if (j < 0) {
+                throw std::runtime_error(format("negative index out of range [0, %d)", ctx->n_outputs));
+            }
+        } else if ((size_t) i >= ctx->output_ids.size()) {
             throw std::runtime_error(format("out of range [0, %lu)", ctx->output_ids.size()));
+        } else {
+            j = ctx->output_ids[i];
         }
-        const int32_t j = ctx->output_ids[i];
 
         if (j < 0) {
             throw std::runtime_error(format("batch.logits[%d] != true", i));
         }
-        if ((size_t) j >= ctx->output_size) {
+        if (j >= ctx->n_outputs) {
             // This should not happen
-            throw std::runtime_error(format("corrupt output buffer (j=%d, output_size=%lu)", j, ctx->output_size));
+            throw std::runtime_error(format("corrupt output buffer (j=%d, n_outputs=%d)", j, ctx->n_outputs));
         }
 
         return ctx->embd + j*ctx->model.hparams.n_embd;
diff --git a/llama.h b/llama.h
index 2250130e2..6a5bbe26d 100644
--- a/llama.h
+++ b/llama.h
@@ -747,8 +747,9 @@ extern "C" {
     // Cols: n_vocab
     LLAMA_API float * llama_get_logits(struct llama_context * ctx);
 
-    // Logits for the ith token. Equivalent to:
+    // Logits for the ith token. For positive indices, Equivalent to:
     // llama_get_logits(ctx) + ctx->output_ids[i]*n_vocab
+    // Negative indicies can be used to access logits in reverse order, -1 is the last logit.
     // returns NULL for invalid ids.
     LLAMA_API float * llama_get_logits_ith(struct llama_context * ctx, int32_t i);
 
@@ -760,8 +761,9 @@ extern "C" {
     // Otherwise, returns NULL.
     LLAMA_API float * llama_get_embeddings(struct llama_context * ctx);
 
-    // Get the embeddings for the ith token. Equivalent to:
+    // Get the embeddings for the ith token. For positive indices, Equivalent to:
     // llama_get_embeddings(ctx) + ctx->output_ids[i]*n_embd
+    // Negative indicies can be used to access embeddings in reverse order, -1 is the last embedding.
     // shape: [n_embd] (1-dimensional)
     // returns NULL for invalid ids.
     LLAMA_API float * llama_get_embeddings_ith(struct llama_context * ctx, int32_t i);

From b73e564b16086845a8b4fffd26e22685d3e0c3db Mon Sep 17 00:00:00 2001
From: Georgi Gerganov <ggerganov@gmail.com>
Date: Mon, 8 Apr 2024 16:23:01 +0300
Subject: [PATCH 4/9] quantize : fix precedence of cli args (#6541)

---
 llama.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/llama.cpp b/llama.cpp
index 9dde3efd0..89ea3fe1a 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -13562,10 +13562,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
             if (!params->pure && ggml_is_quantized(default_type)) {
                 new_type = llama_tensor_get_type(qs, new_type, tensor, ftype);
             }
-            else if (params->token_embedding_type < GGML_TYPE_COUNT && strcmp(tensor->name, "token_embd.weight") == 0) {
+            if (params->token_embedding_type < GGML_TYPE_COUNT && strcmp(tensor->name, "token_embd.weight") == 0) {
                 new_type = params->token_embedding_type;
             }
-            else if (params->output_tensor_type < GGML_TYPE_COUNT && strcmp(tensor->name, "output.weight") == 0) {
+            if (params->output_tensor_type < GGML_TYPE_COUNT && strcmp(tensor->name, "output.weight") == 0) {
                 new_type = params->output_tensor_type;
             }
 

From cecd8d3c98b48f51aaa1d4c729e55bd319f6799c Mon Sep 17 00:00:00 2001
From: kunnis <kunnis@users.noreply.github.com>
Date: Mon, 8 Apr 2024 10:44:19 -0500
Subject: [PATCH 5/9] Comment explaining a decision (#6531)

---
 convert.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/convert.py b/convert.py
index 244eb7582..a37aeb5e5 100755
--- a/convert.py
+++ b/convert.py
@@ -139,7 +139,8 @@ class GGMLFileType(enum.IntEnum):
         dt = GGML_FILE_TYPE_TO_DATA_TYPE.get(self)
         if dt is None:
             raise ValueError(self)
-        # 1D tensors are always F32.
+        # Convert all 1D tensors to F32.  Most of the codebase that takes in 1D tensors only handles F32 tensors, and most of the outputs tensors are F32.
+        #  Also The 1d tensors aren't much of a performance/size issue.  So instead of having to have separate F32 and F16 implementations of both, just convert everything to F32 for now.
         return dt if len(tensor.shape) > 1 else DT_F32
 
 

From cc4a95426d17417d3c83f12bdb514fbe8abe2a88 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov <ggerganov@gmail.com>
Date: Mon, 8 Apr 2024 22:25:49 +0300
Subject: [PATCH 6/9] llama : fix attention layer count sanity check (#6550)

* llama : fix attention layer count sanity check

* llama : fix parentheses in attention layer count sanity check

There was otherwise a warning when compiling.

---------

Co-authored-by: Francis Couture-Harpin <git@compilade.net>
---
 llama.cpp | 9 +++++++--
 1 file changed, 7 insertions(+), 2 deletions(-)

diff --git a/llama.cpp b/llama.cpp
index 89ea3fe1a..b16ddc64c 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -13468,7 +13468,8 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
         const std::string name = ggml_get_name(meta);
 
         // TODO: avoid hardcoded tensor names - use the TN_* constants
-        if (name.find("attn_v.weight") != std::string::npos || name.find("attn_qkv.weight") != std::string::npos) {
+        if (name.find("attn_v.weight")   != std::string::npos ||
+            name.find("attn_qkv.weight") != std::string::npos) {
             ++qs.n_attention_wv;
         } else if (name == LLM_TN(model.arch)(LLM_TENSOR_OUTPUT, "weight")) {
             qs.has_output = true;
@@ -13478,7 +13479,11 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
     qs.n_ffn_down = qs.n_ffn_gate = qs.n_ffn_up = (int)model.hparams.n_layer;
 
     // sanity checks
-    GGML_ASSERT(qs.n_attention_wv == (int)model.hparams.n_layer && "n_attention_wv != n_layer is unexpected");
+    //
+    //  - qs.n_attention_wv == 0                     for Mamba       models
+    //  - qs.n_attention_wv == model.hparams.n_layer for Transformer models
+    //
+    GGML_ASSERT((qs.n_attention_wv == 0 || qs.n_attention_wv == (int)model.hparams.n_layer) && "n_attention_wv is unexpected");
 
     size_t total_size_org = 0;
     size_t total_size_new = 0;

From e11a8999b5690f810c2c99c14347f0834e68c524 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov <ggerganov@gmail.com>
Date: Tue, 9 Apr 2024 09:23:19 +0300
Subject: [PATCH 7/9] license : update copyright notice + add AUTHORS (#6405)

* license : add AUTHORS

* authors : update

* scipts : add LICENSE and gen-authors.sh to sync
---
 AUTHORS                 | 655 ++++++++++++++++++++++++++++++++++++++++
 LICENSE                 |   2 +-
 scripts/gen-authors.sh  |   9 +
 scripts/sync-ggml-am.sh |   7 +
 scripts/sync-ggml.sh    |   3 +
 5 files changed, 675 insertions(+), 1 deletion(-)
 create mode 100644 AUTHORS
 create mode 100755 scripts/gen-authors.sh

diff --git a/AUTHORS b/AUTHORS
new file mode 100644
index 000000000..b029f13da
--- /dev/null
+++ b/AUTHORS
@@ -0,0 +1,655 @@
+# date: Tue Apr  9 09:17:14 EEST 2024
+# this file is auto-generated by scripts/gen-authors.sh
+
+0cc4m <picard12@live.de>
+0xspringtime <110655352+0xspringtime@users.noreply.github.com>
+2f38b454 <dxf@protonmail.com>
+3ooabkhxtn <31479382+3ooabkhxtn@users.noreply.github.com>
+44670 <44670@users.noreply.github.com>
+AN Long <aisk@users.noreply.github.com>
+AT <manyoso@users.noreply.github.com>
+Aarni Koskela <akx@iki.fi>
+Aaron Miller <apage43@ninjawhale.com>
+Aaryaman Vasishta <aaryaman.vasishta@amd.com>
+Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
+Abhishek Gopinath K <31348521+overtunned@users.noreply.github.com>
+Adithya Balaji <adithya.b94@gmail.com>
+AdithyanI <adithyan.i4internet@gmail.com>
+Adrian <smith.adriane@gmail.com>
+Adrian Hesketh <a-h@users.noreply.github.com>
+AidanBeltonS <87009434+AidanBeltonS@users.noreply.github.com>
+Aisuko <urakiny@gmail.com>
+Alberto <57916483+albbus-stack@users.noreply.github.com>
+Alex <awhill19@icloud.com>
+Alex Azarov <alex@azarov.by>
+Alex Azarov <alexander.azarov@mapbox.com>
+Alex Klinkhamer <from.github.com.917@grencez.dev>
+Alex Klinkhamer <git@grencez.dev>
+Alex Nguyen <tiendung@users.noreply.github.com>
+Alex Petenchea <alex.petenchea@gmail.com>
+Alex Renda <alexrenda@users.noreply.github.com>
+Alex von Gluck IV <kallisti5@unixzen.com>
+Alexey Parfenov <zxed@alkatrazstudio.net>
+Ali Chraghi <63465728+alichraghi@users.noreply.github.com>
+Ali Nehzat <ali.nehzat@thanks.dev>
+Ali Tariq <ali.tariq@10xengineers.ai>
+Alon <alonfaraj@gmail.com>
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+Ashraful Islam <ashraful.meche@gmail.com>
+Atsushi Tatsuma <yoshoku@outlook.com>
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+Cuong Trinh Manh <nguoithichkhampha@gmail.com>
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+DannyDaemonic <DannyDaemonic@gmail.com>
+Dat Quoc Nguyen <2412555+datquocnguyen@users.noreply.github.com>
+Dave Della Costa <ddellacosta+github@gmail.com>
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+Genkagaku.GPT <hlhr202@163.com>
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+thement <40525767+thement@users.noreply.github.com>
+tjohnman <tjohnman@users.noreply.github.com>
+tslmy <tslmy@users.noreply.github.com>
+ubik2 <ubik2@users.noreply.github.com>
+uint256_t <konndennsa@gmail.com>
+uint256_t <maekawatoshiki1017@gmail.com>
+unbounded <haakon@likedan.net>
+valiray <133289098+valiray@users.noreply.github.com>
+vodkaslime <646329483@qq.com>
+vvhg1 <94630311+vvhg1@users.noreply.github.com>
+vxiiduu <73044267+vxiiduu@users.noreply.github.com>
+wbpxre150 <100937007+wbpxre150@users.noreply.github.com>
+whoreson <139810751+whoreson@users.noreply.github.com>
+wonjun Jang <strutive07@gmail.com>
+wzy <32936898+Freed-Wu@users.noreply.github.com>
+xaedes <xaedes@gmail.com>
+xaedes <xaedes@googlemail.com>
+xloem <0xloem@gmail.com>
+yangli2 <yangli2@gmail.com>
+yuiseki <yuiseki@gmail.com>
+zakkor <edward.partenie@gmail.com>
+zhouwg <6889919+zhouwg@users.noreply.github.com>
+zrm <trustiosity.zrm@gmail.com>
+源文雨 <41315874+fumiama@users.noreply.github.com>
+Нияз Гарифзянов <112617865+garrnizon@users.noreply.github.com>
diff --git a/LICENSE b/LICENSE
index 76f67efdc..acb96ce78 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2023 Georgi Gerganov
+Copyright (c) 2023-2024 The ggml authors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
diff --git a/scripts/gen-authors.sh b/scripts/gen-authors.sh
new file mode 100755
index 000000000..3ef8391cc
--- /dev/null
+++ b/scripts/gen-authors.sh
@@ -0,0 +1,9 @@
+#!/bin/bash
+
+printf "# date: $(date)\n" > AUTHORS
+printf "# this file is auto-generated by scripts/gen-authors.sh\n\n" >> AUTHORS
+
+git log --format='%an <%ae>' --reverse --date=short master | awk '!seen[$0]++' | sort >> AUTHORS
+
+# if necessary, update your name here. for example: jdoe -> John Doe
+sed -i '' 's/^jdoe/John Doe/g' AUTHORS
diff --git a/scripts/sync-ggml-am.sh b/scripts/sync-ggml-am.sh
index 3ae7f460d..7c157eb4c 100755
--- a/scripts/sync-ggml-am.sh
+++ b/scripts/sync-ggml-am.sh
@@ -66,6 +66,8 @@ while read c; do
         tests/test-quantize-fns.cpp \
         tests/test-quantize-perf.cpp \
         tests/test-backend-ops.cpp \
+        LICENSE \
+        scripts/gen-authors.sh \
         >> $SRC_LLAMA/ggml-src.patch
 done < $SRC_LLAMA/ggml-commits
 
@@ -123,6 +125,9 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
     # tests/test-quantize-fns.cpp  -> tests/test-quantize-fns.cpp
     # tests/test-quantize-perf.cpp -> tests/test-quantize-perf.cpp
     # tests/test-backend-ops.cpp   -> tests/test-backend-ops.cpp
+    #
+    # LICENSE                      -> LICENSE
+    # scripts/gen-authors.sh       -> scripts/gen-authors.sh
 
     cat ggml-src.patch | sed \
         -e 's/src\/ggml\.c/ggml.c/g' \
@@ -156,6 +161,8 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
         -e 's/tests\/test-quantize-fns\.cpp/tests\/test-quantize-fns.cpp/g' \
         -e 's/tests\/test-quantize-perf\.cpp/tests\/test-quantize-perf.cpp/g' \
         -e 's/tests\/test-backend-ops\.cpp/tests\/test-backend-ops.cpp/g' \
+        -e 's/LICENSE/LICENSE/g' \
+        -e 's/scripts\/gen-authors\.sh/scripts\/gen-authors.sh/g' \
         > ggml-src.patch.tmp
     mv ggml-src.patch.tmp ggml-src.patch
 
diff --git a/scripts/sync-ggml.sh b/scripts/sync-ggml.sh
index d8fdaadf7..80c43976f 100755
--- a/scripts/sync-ggml.sh
+++ b/scripts/sync-ggml.sh
@@ -31,3 +31,6 @@ cp -rpv ../ggml/include/ggml/ggml-backend.h ./ggml-backend.h
 cp -rpv ../ggml/tests/test-opt.cpp         ./tests/test-opt.cpp
 cp -rpv ../ggml/tests/test-grad0.cpp       ./tests/test-grad0.cpp
 cp -rpv ../ggml/tests/test-backend-ops.cpp ./tests/test-backend-ops.cpp
+
+cp -rpv ../LICENSE                         ./LICENSE
+cp -rpv ../ggml/scripts/gen-authors.sh     ./scripts/gen-authors.sh

From 5dc9dd7152dedc6046b646855585bd070c91e8c8 Mon Sep 17 00:00:00 2001
From: Carolinabanana <140120812+Carolinabanana@users.noreply.github.com>
Date: Tue, 9 Apr 2024 09:16:13 +0100
Subject: [PATCH 8/9] llama : add Command R Plus support (#6491)

* Add Command R Plus GGUF

* Add Command R Plus GGUF

* Loading works up to LayerNorm2D

* Export new tensors in 1D so they are not quantized.

* Fix embedding layer based on Noeda's example

* Whitespace

* Add line

* Fix unexpected tokens on MPS. Re-add F16 fix. ((Noeda)

* dranger003: Fix block index overflow in CUDA dequantizing.

* Reverted blocked multiplication code as it still has issues and could affect other Llama arches

* export norms as f32

* fix overflow issues during quant and other cleanup

* Type convention

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* dranger003: Fix more int overflow during quant.

---------

Co-authored-by: S <seast@Ss-Mac-Studio.local>
Co-authored-by: S <s@example.com>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---
 convert-hf-to-gguf.py          |   2 +-
 ggml-cuda.cu                   |   6 +-
 ggml-cuda/common.cuh           |   2 +-
 ggml-cuda/convert.cu           |  74 ++++----
 ggml-cuda/convert.cuh          |   2 +-
 ggml-cuda/dequantize.cuh       |  10 +-
 ggml-cuda/dmmv.cu              |   6 +-
 ggml-cuda/quantize.cu          |  16 +-
 ggml-cuda/quantize.cuh         |   2 +-
 ggml-quants.c                  | 310 ++++++++++++++++-----------------
 ggml-quants.h                  | 148 ++++++++--------
 ggml.c                         |  16 +-
 ggml.h                         |  14 +-
 gguf-py/gguf/constants.py      |   2 +
 gguf-py/gguf/tensor_mapping.py |   2 +
 llama.cpp                      |  64 +++++--
 16 files changed, 358 insertions(+), 318 deletions(-)

diff --git a/convert-hf-to-gguf.py b/convert-hf-to-gguf.py
index 7e601170e..37af6328a 100755
--- a/convert-hf-to-gguf.py
+++ b/convert-hf-to-gguf.py
@@ -160,7 +160,7 @@ class Model(ABC):
                 data = data.astype(np.float32)
 
             # TODO: Why cant we use these float16 as-is? There should be not reason to store float16 as float32
-            if self.ftype == 1 and data_dtype == np.float16 and n_dims == 1:
+            if self.ftype == 1 and data_dtype == np.float16 and (n_dims == 1 or new_name.endswith("_norm.weight")):
                 data = data.astype(np.float32)
 
             # if f16 desired, convert any float32 2-dim weight tensors to float16
diff --git a/ggml-cuda.cu b/ggml-cuda.cu
index ce28cb55d..bff8ad9d9 100644
--- a/ggml-cuda.cu
+++ b/ggml-cuda.cu
@@ -1225,7 +1225,7 @@ static void ggml_cuda_op_mul_mat_cublas(
 
     // the main device has a larger memory buffer to hold the results from all GPUs
     // ldc == nrows of the matrix that cuBLAS writes into
-    int ldc = id == ctx.device ? ne0 : row_diff;
+    int64_t ldc = id == ctx.device ? ne0 : row_diff;
 
     const int compute_capability = ggml_cuda_info().devices[id].cc;
 
@@ -1377,8 +1377,8 @@ static void ggml_cuda_op_mul_mat(
     const int64_t ne0 = dst->ne[0];
     const int64_t ne1 = dst->ne[1];
 
-    const int nb2 = dst->nb[2];
-    const int nb3 = dst->nb[3];
+    const int64_t nb2 = dst->nb[2];
+    const int64_t nb3 = dst->nb[3];
 
     GGML_ASSERT(ggml_backend_buffer_is_cuda(dst->buffer));
     GGML_ASSERT(ggml_backend_buffer_is_cuda(src1->buffer));
diff --git a/ggml-cuda/common.cuh b/ggml-cuda/common.cuh
index b98d7cbd0..481065b2a 100644
--- a/ggml-cuda/common.cuh
+++ b/ggml-cuda/common.cuh
@@ -394,7 +394,7 @@ static __device__ __forceinline__ int __dp4a(const int a, const int b, int c) {
 // TODO: move to ggml-common.h
 static const __device__ int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
 
-typedef void (*dequantize_kernel_t)(const void * vx, const int ib, const int iqs, dfloat2 & v);
+typedef void (*dequantize_kernel_t)(const void * vx, const int64_t ib, const int iqs, dfloat2 & v);
 
 
 //////////////////////
diff --git a/ggml-cuda/convert.cu b/ggml-cuda/convert.cu
index 18a31edc3..ed4fa2748 100644
--- a/ggml-cuda/convert.cu
+++ b/ggml-cuda/convert.cu
@@ -4,14 +4,14 @@
 #define CUDA_Q8_0_NE_ALIGN 2048
 
 template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t>
-static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __restrict__ y, const int k) {
-    const int i = 2*(blockDim.x*blockIdx.x + threadIdx.x);
+static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k) {
+    const int64_t i = 2*(blockDim.x*blockIdx.x + threadIdx.x);
 
     if (i >= k) {
         return;
     }
 
-    const int ib = i/qk; // block index
+    const int64_t ib = i/qk; // block index
     const int iqs = (i%qk)/qr; // quant index
     const int iybs = i - i%qk; // y block start index
     const int y_offset = qr == 1 ? 1 : qk/2;
@@ -25,7 +25,7 @@ static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __
 }
 
 template <bool need_check>
-static __global__ void dequantize_block_q8_0_f16(const void * __restrict__ vx, half * __restrict__ y, const int k) {
+static __global__ void dequantize_block_q8_0_f16(const void * __restrict__ vx, half * __restrict__ y, const int64_t k) {
 #if __CUDA_ARCH__ >= CC_PASCAL
     constexpr int nint = CUDA_Q8_0_NE_ALIGN/sizeof(int) + WARP_SIZE;
 
@@ -68,13 +68,13 @@ static __global__ void dequantize_block_q8_0_f16(const void * __restrict__ vx, h
 template<typename dst_t>
 static __global__ void dequantize_block_q4_0(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) {
 
-    const int i = blockIdx.x;
+    const int64_t i = blockIdx.x;
 
     // assume 32 threads
     const int tid = threadIdx.x;
     const int il  = tid/8;
     const int ir  = tid%8;
-    const int ib = 8*i + ir;
+    const int64_t ib = 8*i + ir;
     if (ib >= nb32) {
         return;
     }
@@ -96,13 +96,13 @@ static __global__ void dequantize_block_q4_0(const void * __restrict__ vx, dst_t
 template<typename dst_t>
 static __global__ void dequantize_block_q4_1(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) {
 
-    const int i = blockIdx.x;
+    const int64_t i = blockIdx.x;
 
     // assume 32 threads
     const int tid = threadIdx.x;
     const int il  = tid/8;
     const int ir  = tid%8;
-    const int ib = 8*i + ir;
+    const int64_t ib = 8*i + ir;
     if (ib >= nb32) {
         return;
     }
@@ -313,14 +313,14 @@ template<typename dst_t>
 static __global__ void dequantize_block_q6_K(const void * __restrict__ vx, dst_t * __restrict__ yy) {
     const block_q6_K * x = (const block_q6_K *) vx;
 
-    const int i = blockIdx.x;
+    const int64_t i = blockIdx.x;
 #if QK_K == 256
 
     // assume 64 threads - this is very slightly better than the one below
-    const int tid = threadIdx.x;
-    const int ip  = tid/32;   // ip is 0 or 1
-    const int il  = tid - 32*ip; // 0...32
-    const int is  = 8*ip + il/16;
+    const int64_t tid = threadIdx.x;
+    const int64_t ip  = tid/32;   // ip is 0 or 1
+    const int64_t il  = tid - 32*ip; // 0...32
+    const int64_t is  = 8*ip + il/16;
 
     dst_t * y = yy + i*QK_K + 128*ip + il;
 
@@ -337,9 +337,9 @@ static __global__ void dequantize_block_q6_K(const void * __restrict__ vx, dst_t
 #else
 
     // assume 32 threads
-    const int tid = threadIdx.x;
-    const int ip  = tid/16;         // 0 or 1
-    const int il  = tid - 16*ip;    // 0...15
+    const int64_t tid = threadIdx.x;
+    const int64_t ip  = tid/16;         // 0 or 1
+    const int64_t il  = tid - 16*ip;    // 0...15
 
     dst_t * y = yy + i*QK_K + 16*ip + il;
 
@@ -571,12 +571,12 @@ static __global__ void dequantize_block_iq4_xs(const void * __restrict__ vx, dst
 #endif
 
 template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t>
-static void dequantize_block_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int k, cudaStream_t stream) {
+static void dequantize_block_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k, cudaStream_t stream) {
     const int num_blocks = (k + 2*CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / (2*CUDA_DEQUANTIZE_BLOCK_SIZE);
     dequantize_block<qk, qr, dequantize_kernel><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>>(vx, y, k);
 }
 
-static void dequantize_block_q8_0_f16_cuda(const void * __restrict__ vx, half * __restrict__ y, const int k, cudaStream_t stream) {
+static void dequantize_block_q8_0_f16_cuda(const void * __restrict__ vx, half * __restrict__ y, const int64_t k, cudaStream_t stream) {
     const int num_blocks = (k + CUDA_Q8_0_NE_ALIGN - 1) / CUDA_Q8_0_NE_ALIGN;
     if (k % CUDA_Q8_0_NE_ALIGN == 0) {
         const bool need_check = false;
@@ -588,7 +588,7 @@ static void dequantize_block_q8_0_f16_cuda(const void * __restrict__ vx, half *
 }
 
 template<typename dst_t>
-static void dequantize_row_q2_K_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q2_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
 #if QK_K == 256
     dequantize_block_q2_K<<<nb, 64, 0, stream>>>(vx, y);
@@ -598,7 +598,7 @@ static void dequantize_row_q2_K_cuda(const void * vx, dst_t * y, const int k, cu
 }
 
 template<typename dst_t>
-static void dequantize_row_q3_K_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q3_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
 #if QK_K == 256
     dequantize_block_q3_K<<<nb, 64, 0, stream>>>(vx, y);
@@ -608,27 +608,27 @@ static void dequantize_row_q3_K_cuda(const void * vx, dst_t * y, const int k, cu
 }
 
 template<typename dst_t>
-static void dequantize_row_q4_0_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q4_0_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb32 = k / 32;
     const int nb = (k + 255) / 256;
     dequantize_block_q4_0<<<nb, 32, 0, stream>>>(vx, y, nb32);
 }
 
 template<typename dst_t>
-static void dequantize_row_q4_1_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q4_1_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb32 = k / 32;
     const int nb = (k + 255) / 256;
     dequantize_block_q4_1<<<nb, 32, 0, stream>>>(vx, y, nb32);
 }
 
 template<typename dst_t>
-static void dequantize_row_q4_K_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q4_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_q4_K<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_q5_K_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q5_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
 #if QK_K == 256
     dequantize_block_q5_K<<<nb, 64, 0, stream>>>(vx, y);
@@ -638,7 +638,7 @@ static void dequantize_row_q5_K_cuda(const void * vx, dst_t * y, const int k, cu
 }
 
 template<typename dst_t>
-static void dequantize_row_q6_K_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_q6_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
 #if QK_K == 256
     dequantize_block_q6_K<<<nb, 64, 0, stream>>>(vx, y);
@@ -648,55 +648,55 @@ static void dequantize_row_q6_K_cuda(const void * vx, dst_t * y, const int k, cu
 }
 
 template<typename dst_t>
-static void dequantize_row_iq2_xxs_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq2_xxs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq2_xxs<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq2_xs_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq2_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq2_xs<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq2_s_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq2_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq2_s<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq3_xxs_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq3_xxs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq3_xxs<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq3_s_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq3_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq3_s<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq1_s_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq1_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq1_s<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq4_nl_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq4_nl_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = (k + QK_K - 1) / QK_K;
     dequantize_block_iq4_nl<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq1_m_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq1_m_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = k / QK_K;
     dequantize_block_iq1_m<<<nb, 32, 0, stream>>>(vx, y);
 }
 
 template<typename dst_t>
-static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int k, cudaStream_t stream) {
+static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) {
     const int nb = (k + QK_K - 1) / QK_K;
 #if QK_K == 64
     dequantize_block_iq4_nl<<<nb, 32, 0, stream>>>(vx, y);
@@ -706,8 +706,8 @@ static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int k,
 }
 
 template <typename src_t, typename dst_t>
-static __global__ void convert_unary(const void * __restrict__ vx, dst_t * __restrict__ y, const int k) {
-    const int i = blockDim.x*blockIdx.x + threadIdx.x;
+static __global__ void convert_unary(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k) {
+    const int64_t i = (int64_t)blockDim.x*blockIdx.x + threadIdx.x;
 
     if (i >= k) {
         return;
@@ -719,7 +719,7 @@ static __global__ void convert_unary(const void * __restrict__ vx, dst_t * __res
 }
 
 template <typename src_t, typename dst_t>
-static void convert_unary_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int k, cudaStream_t stream) {
+static void convert_unary_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k, cudaStream_t stream) {
     const int num_blocks = (k + CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / CUDA_DEQUANTIZE_BLOCK_SIZE;
     convert_unary<src_t><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>>(vx, y, k);
 }
diff --git a/ggml-cuda/convert.cuh b/ggml-cuda/convert.cuh
index db34c0be9..5394be9f1 100644
--- a/ggml-cuda/convert.cuh
+++ b/ggml-cuda/convert.cuh
@@ -3,7 +3,7 @@
 #define CUDA_DEQUANTIZE_BLOCK_SIZE 256
 
 template<typename T>
-using to_t_cuda_t = void (*)(const void * __restrict__ x, T * __restrict__ y, int k, cudaStream_t stream);
+using to_t_cuda_t = void (*)(const void * __restrict__ x, T * __restrict__ y, int64_t k, cudaStream_t stream);
 
 typedef to_t_cuda_t<float> to_fp32_cuda_t;
 typedef to_t_cuda_t<half> to_fp16_cuda_t;
diff --git a/ggml-cuda/dequantize.cuh b/ggml-cuda/dequantize.cuh
index b54400632..bd3c2d9db 100644
--- a/ggml-cuda/dequantize.cuh
+++ b/ggml-cuda/dequantize.cuh
@@ -1,6 +1,6 @@
 #include "common.cuh"
 
-static __device__ __forceinline__ void dequantize_q4_0(const void * vx, const int ib, const int iqs, dfloat2 & v){
+static __device__ __forceinline__ void dequantize_q4_0(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
     const block_q4_0 * x = (const block_q4_0 *) vx;
 
     const dfloat d = x[ib].d;
@@ -19,7 +19,7 @@ static __device__ __forceinline__ void dequantize_q4_0(const void * vx, const in
 #endif // GGML_CUDA_F16
 }
 
-static __device__ __forceinline__ void dequantize_q4_1(const void * vx, const int ib, const int iqs, dfloat2 & v){
+static __device__ __forceinline__ void dequantize_q4_1(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
     const block_q4_1 * x = (const block_q4_1 *) vx;
 
     const dfloat d = __low2half(x[ib].dm);
@@ -39,7 +39,7 @@ static __device__ __forceinline__ void dequantize_q4_1(const void * vx, const in
 #endif // GGML_CUDA_F16
 }
 
-static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const int ib, const int iqs, dfloat2 & v){
+static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
     const block_q5_0 * x = (const block_q5_0 *) vx;
 
     const dfloat d = x[ib].d;
@@ -62,7 +62,7 @@ static __device__ __forceinline__ void dequantize_q5_0(const void * vx, const in
 #endif // GGML_CUDA_F16
 }
 
-static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const int ib, const int iqs, dfloat2 & v){
+static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
     const block_q5_1 * x = (const block_q5_1 *) vx;
 
     const dfloat d = __low2half(x[ib].dm);
@@ -86,7 +86,7 @@ static __device__ __forceinline__ void dequantize_q5_1(const void * vx, const in
 #endif // GGML_CUDA_F16
 }
 
-static __device__ __forceinline__ void dequantize_q8_0(const void * vx, const int ib, const int iqs, dfloat2 & v){
+static __device__ __forceinline__ void dequantize_q8_0(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
     const block_q8_0 * x = (const block_q8_0 *) vx;
 
     const dfloat d = x[ib].d;
diff --git a/ggml-cuda/dmmv.cu b/ggml-cuda/dmmv.cu
index 0b17e3cb9..7313e3e17 100644
--- a/ggml-cuda/dmmv.cu
+++ b/ggml-cuda/dmmv.cu
@@ -565,7 +565,7 @@ static __global__ void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx,
     }
 }
 
-static __device__ void convert_f16(const void * vx, const int ib, const int iqs, dfloat2 & v){
+static __device__ void convert_f16(const void * vx, const int64_t ib, const int iqs, dfloat2 & v){
     const half * x = (const half *) vx;
 
     // automatic half -> float type cast if dfloat == float
@@ -577,7 +577,7 @@ template <int qk, int qr, dequantize_kernel_t dequantize_kernel>
 static __global__ void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat * __restrict__ y, float * __restrict__ dst, const int ncols, const int nrows) {
     // qk = quantized weights per x block
     // qr = number of quantized weights per data value in x block
-    const int row = blockIdx.x*blockDim.y + threadIdx.y;
+    const int64_t row = (int64_t)blockIdx.x*blockDim.y + threadIdx.y;
 
     if (row >= nrows) {
         return;
@@ -598,7 +598,7 @@ static __global__ void dequantize_mul_mat_vec(const void * __restrict__ vx, cons
 
     for (int i = 0; i < ncols; i += iter_stride) {
         const int col = i + vals_per_iter*tid;
-        const int ib = (row*ncols + col)/qk; // x block index
+        const int64_t ib = ((int64_t)row*ncols + col)/qk; // x block index
         const int iqs = (col%qk)/qr; // x quant index
         const int iybs = col - col%qk; // y block start index
 
diff --git a/ggml-cuda/quantize.cu b/ggml-cuda/quantize.cu
index a1fbc9932..7578c4b6c 100644
--- a/ggml-cuda/quantize.cu
+++ b/ggml-cuda/quantize.cu
@@ -1,20 +1,20 @@
 #include "quantize.cuh"
 
-static __global__ void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy, const int kx, const int kx_padded) {
-    const int ix = blockDim.x*blockIdx.x + threadIdx.x;
+static __global__ void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy, const int64_t kx, const int64_t kx_padded) {
+    const int64_t ix = (int64_t)blockDim.x*blockIdx.x + threadIdx.x;
 
     if (ix >= kx_padded) {
         return;
     }
 
-    const int iy = blockDim.y*blockIdx.y + threadIdx.y;
+    const int64_t iy = (int64_t)blockDim.y*blockIdx.y + threadIdx.y;
 
-    const int i_padded = iy*kx_padded + ix;
+    const int64_t i_padded = (int64_t)iy*kx_padded + ix;
 
     block_q8_1 * y = (block_q8_1 *) vy;
 
-    const int ib = i_padded / QK8_1; // block index
-    const int iqs = i_padded % QK8_1; // quant index
+    const int64_t ib = i_padded / QK8_1; // block index
+    const int64_t iqs = i_padded % QK8_1; // quant index
 
     const float xi = ix < kx ? x[iy*kx + ix] : 0.0f;
     float amax = fabsf(xi);
@@ -36,8 +36,8 @@ static __global__ void quantize_q8_1(const float * __restrict__ x, void * __rest
     reinterpret_cast<half&>(y[ib].ds.y) = sum;
 }
 
-void quantize_row_q8_1_cuda(const float * x, void * vy, const int kx, const int ky, const int kx_padded, cudaStream_t stream) {
-    const int block_num_x = (kx_padded + CUDA_QUANTIZE_BLOCK_SIZE - 1) / CUDA_QUANTIZE_BLOCK_SIZE;
+void quantize_row_q8_1_cuda(const float * x, void * vy, const int64_t kx, const int64_t ky, const int64_t kx_padded, cudaStream_t stream) {
+    const int64_t block_num_x = (kx_padded + CUDA_QUANTIZE_BLOCK_SIZE - 1) / CUDA_QUANTIZE_BLOCK_SIZE;
     const dim3 num_blocks(block_num_x, ky, 1);
     const dim3 block_size(CUDA_QUANTIZE_BLOCK_SIZE, 1, 1);
     quantize_q8_1<<<num_blocks, block_size, 0, stream>>>(x, vy, kx, kx_padded);
diff --git a/ggml-cuda/quantize.cuh b/ggml-cuda/quantize.cuh
index adb89c83a..b37a4752f 100644
--- a/ggml-cuda/quantize.cuh
+++ b/ggml-cuda/quantize.cuh
@@ -2,4 +2,4 @@
 
 #define CUDA_QUANTIZE_BLOCK_SIZE 256
 
-void quantize_row_q8_1_cuda(const float * x, void * vy, const int kx, const int ky, const int kx_padded, cudaStream_t stream);
+void quantize_row_q8_1_cuda(const float * x, void * vy, const int64_t kx, const int64_t ky, const int64_t kx_padded, cudaStream_t stream);
diff --git a/ggml-quants.c b/ggml-quants.c
index f2e6c4bd1..32e84434a 100644
--- a/ggml-quants.c
+++ b/ggml-quants.c
@@ -544,7 +544,7 @@ static const uint64_t table_b2b_1[1 << 8] = { B8(10, 00) }; // (!b) << 4
 #endif
 
 // reference implementation for deterministic creation of model files
-void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict y, int k) {
+void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict y, int64_t k) {
     static const int qk = QK4_0;
 
     assert(k % qk == 0);
@@ -581,12 +581,12 @@ void quantize_row_q4_0_reference(const float * restrict x, block_q4_0 * restrict
     }
 }
 
-void quantize_row_q4_0(const float * restrict x, void * restrict y, int k) {
+void quantize_row_q4_0(const float * restrict x, void * restrict y, int64_t k) {
     quantize_row_q4_0_reference(x, y, k);
 }
 
 
-void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * restrict y, int k) {
+void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * restrict y, int64_t k) {
     const int qk = QK4_1;
 
     assert(k % qk == 0);
@@ -623,11 +623,11 @@ void quantize_row_q4_1_reference(const float * restrict x, block_q4_1 * restrict
     }
 }
 
-void quantize_row_q4_1(const float * restrict x, void * restrict y, int k) {
+void quantize_row_q4_1(const float * restrict x, void * restrict y, int64_t k) {
     quantize_row_q4_1_reference(x, y, k);
 }
 
-void quantize_row_q5_0_reference(const float * restrict x, block_q5_0 * restrict y, int k) {
+void quantize_row_q5_0_reference(const float * restrict x, block_q5_0 * restrict y, int64_t k) {
     static const int qk = QK5_0;
 
     assert(k % qk == 0);
@@ -671,11 +671,11 @@ void quantize_row_q5_0_reference(const float * restrict x, block_q5_0 * restrict
     }
 }
 
-void quantize_row_q5_0(const float * restrict x, void * restrict y, int k) {
+void quantize_row_q5_0(const float * restrict x, void * restrict y, int64_t k) {
     quantize_row_q5_0_reference(x, y, k);
 }
 
-void quantize_row_q5_1_reference(const float * restrict x, block_q5_1 * restrict y, int k) {
+void quantize_row_q5_1_reference(const float * restrict x, block_q5_1 * restrict y, int64_t k) {
     const int qk = QK5_1;
 
     assert(k % qk == 0);
@@ -719,12 +719,12 @@ void quantize_row_q5_1_reference(const float * restrict x, block_q5_1 * restrict
     }
 }
 
-void quantize_row_q5_1(const float * restrict x, void * restrict y, int k) {
+void quantize_row_q5_1(const float * restrict x, void * restrict y, int64_t k) {
     quantize_row_q5_1_reference(x, y, k);
 }
 
 // reference implementation for deterministic creation of model files
-void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * restrict y, int k) {
+void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * restrict y, int64_t k) {
     assert(k % QK8_0 == 0);
     const int nb = k / QK8_0;
 
@@ -749,7 +749,7 @@ void quantize_row_q8_0_reference(const float * restrict x, block_q8_0 * restrict
     }
 }
 
-void quantize_row_q8_0(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k) {
     assert(QK8_0 == 32);
     assert(k % QK8_0 == 0);
     const int nb = k / QK8_0;
@@ -938,7 +938,7 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int k) {
 }
 
 // reference implementation for deterministic creation of model files
-void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * restrict y, int k) {
+void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * restrict y, int64_t k) {
     assert(QK8_1 == 32);
     assert(k % QK8_1 == 0);
     const int nb = k / QK8_1;
@@ -973,7 +973,7 @@ void quantize_row_q8_1_reference(const float * restrict x, block_q8_1 * restrict
     }
 }
 
-void quantize_row_q8_1(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK8_1 == 0);
     const int nb = k / QK8_1;
 
@@ -1192,7 +1192,7 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int k) {
 #endif
 }
 
-void dequantize_row_q4_0(const block_q4_0 * restrict x, float * restrict y, int k) {
+void dequantize_row_q4_0(const block_q4_0 * restrict x, float * restrict y, int64_t k) {
     static const int qk = QK4_0;
 
     assert(k % qk == 0);
@@ -1212,7 +1212,7 @@ void dequantize_row_q4_0(const block_q4_0 * restrict x, float * restrict y, int
     }
 }
 
-void dequantize_row_q4_1(const block_q4_1 * restrict x, float * restrict y, int k) {
+void dequantize_row_q4_1(const block_q4_1 * restrict x, float * restrict y, int64_t k) {
     static const int qk = QK4_1;
 
     assert(k % qk == 0);
@@ -1233,7 +1233,7 @@ void dequantize_row_q4_1(const block_q4_1 * restrict x, float * restrict y, int
     }
 }
 
-void dequantize_row_q5_0(const block_q5_0 * restrict x, float * restrict y, int k) {
+void dequantize_row_q5_0(const block_q5_0 * restrict x, float * restrict y, int64_t k) {
     static const int qk = QK5_0;
 
     assert(k % qk == 0);
@@ -1259,7 +1259,7 @@ void dequantize_row_q5_0(const block_q5_0 * restrict x, float * restrict y, int
     }
 }
 
-void dequantize_row_q5_1(const block_q5_1 * restrict x, float * restrict y, int k) {
+void dequantize_row_q5_1(const block_q5_1 * restrict x, float * restrict y, int64_t k) {
     static const int qk = QK5_1;
 
     assert(k % qk == 0);
@@ -1286,7 +1286,7 @@ void dequantize_row_q5_1(const block_q5_1 * restrict x, float * restrict y, int
     }
 }
 
-void dequantize_row_q8_0(const block_q8_0 * restrict x, float * restrict y, int k) {
+void dequantize_row_q8_0(const block_q8_0 * restrict x, float * restrict y, int64_t k) {
     static const int qk = QK8_0;
 
     assert(k % qk == 0);
@@ -1581,7 +1581,7 @@ static inline void get_scale_min_k4(int j, const uint8_t * restrict q, uint8_t *
 
 //========================- 2-bit (de)-quantization
 
-void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict y, int k) {
+void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -1658,7 +1658,7 @@ void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict
     }
 }
 
-void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -1704,7 +1704,7 @@ void dequantize_row_q2_K(const block_q2_K * restrict x, float * restrict y, int
     }
 }
 
-void quantize_row_q2_K(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q2_K(const float * restrict x, void * restrict vy, int64_t k) {
     quantize_row_q2_K_reference(x, vy, k);
 }
 
@@ -1960,14 +1960,14 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
     }
 }
 
-size_t quantize_q2_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q2_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q2_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q2_K_reference(src, dst, nrow*n_per_row);
+        quantize_row_q2_K_reference(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
-        for (int row = 0; row < nrow; ++row) {
+        for (int64_t row = 0; row < nrow; ++row) {
             quantize_row_q2_K_impl(src, (block_q2_K*)qrow, n_per_row, quant_weights);
             src += n_per_row;
             qrow += row_size;
@@ -1978,7 +1978,7 @@ size_t quantize_q2_K(const float * restrict src, void * restrict dst, int nrow,
 
 //========================= 3-bit (de)-quantization
 
-void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict y, int k) {
+void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2092,7 +2092,7 @@ void quantize_row_q3_K_reference(const float * restrict x, block_q3_K * restrict
 }
 
 #if QK_K == 256
-void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2142,7 +2142,7 @@ void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int
     }
 }
 #else
-void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     assert(QK_K == 64);
     const int nb = k / QK_K;
@@ -2175,11 +2175,11 @@ void dequantize_row_q3_K(const block_q3_K * restrict x, float * restrict y, int
 }
 #endif
 
-void quantize_row_q3_K(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q3_K(const float * restrict x, void * restrict vy, int64_t k) {
     quantize_row_q3_K_reference(x, vy, k);
 }
 
-static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restrict y, int n_per_row, const float * restrict quant_weights) {
+static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restrict y, int64_t n_per_row, const float * restrict quant_weights) {
 #if QK_K != 256
     (void)quant_weights;
     quantize_row_q3_K_reference(x, y, n_per_row);
@@ -2268,14 +2268,14 @@ static void quantize_row_q3_K_impl(const float * restrict x, block_q3_K * restri
 #endif
 }
 
-size_t quantize_q3_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q3_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q3_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q3_K_reference(src, dst, nrow*n_per_row);
+        quantize_row_q3_K_reference(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
-        for (int row = 0; row < nrow; ++row) {
+        for (int64_t row = 0; row < nrow; ++row) {
             quantize_row_q3_K_impl(src, (block_q3_K*)qrow, n_per_row, quant_weights);
             src += n_per_row;
             qrow += row_size;
@@ -2286,7 +2286,7 @@ size_t quantize_q3_K(const float * restrict src, void * restrict dst, int nrow,
 
 // ====================== 4-bit (de)-quantization
 
-void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict y, int k) {
+void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2393,7 +2393,7 @@ void quantize_row_q4_K_reference(const float * restrict x, block_q4_K * restrict
     }
 }
 
-void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     const int nb = k / QK_K;
 
@@ -2432,19 +2432,19 @@ void dequantize_row_q4_K(const block_q4_K * restrict x, float * restrict y, int
     }
 }
 
-void quantize_row_q4_K(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q4_K(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_q4_K * restrict y = vy;
     quantize_row_q4_K_reference(x, y, k);
 }
 
-static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restrict y, int64_t n_per_row, const float * quant_weights) {
 #if QK_K != 256
     (void)quant_weights;
     quantize_row_q4_K_reference(x, y, n_per_row);
 #else
     assert(n_per_row % QK_K == 0);
-    const int nb = n_per_row / QK_K;
+    const int64_t nb = n_per_row / QK_K;
 
     uint8_t L[QK_K];
     uint8_t Laux[32];
@@ -2516,14 +2516,14 @@ static void quantize_row_q4_K_impl(const float * restrict x, block_q4_K * restri
 #endif
 }
 
-size_t quantize_q4_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q4_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q4_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q4_K_reference(src, dst, nrow*n_per_row);
+        quantize_row_q4_K_reference(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
-        for (int row = 0; row < nrow; ++row) {
+        for (int64_t row = 0; row < nrow; ++row) {
             quantize_row_q4_K_impl(src, (block_q4_K*)qrow, n_per_row, quant_weights);
             src += n_per_row;
             qrow += row_size;
@@ -2534,9 +2534,9 @@ size_t quantize_q4_K(const float * restrict src, void * restrict dst, int nrow,
 
 // ====================== 5-bit (de)-quantization
 
-void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict y, int k) {
+void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
 #if QK_K == 256
     uint8_t L[QK_K];
@@ -2676,9 +2676,9 @@ void quantize_row_q5_K_reference(const float * restrict x, block_q5_K * restrict
     }
 }
 
-void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
 
@@ -2721,19 +2721,19 @@ void dequantize_row_q5_K(const block_q5_K * restrict x, float * restrict y, int
     }
 }
 
-void quantize_row_q5_K(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q5_K(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_q5_K * restrict y = vy;
     quantize_row_q5_K_reference(x, y, k);
 }
 
-static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restrict y, int64_t n_per_row, const float * quant_weights) {
 #if QK_K != 256
     (void)quant_weights;
     quantize_row_q5_K_reference(x, y, n_per_row);
 #else
     assert(n_per_row % QK_K == 0);
-    const int nb = n_per_row / QK_K;
+    const int64_t nb = n_per_row / QK_K;
 
     uint8_t L[QK_K];
     uint8_t Laux[32];
@@ -2825,14 +2825,14 @@ static void quantize_row_q5_K_impl(const float * restrict x, block_q5_K * restri
 #endif
 }
 
-size_t quantize_q5_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q5_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q5_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q5_K_reference(src, dst, nrow*n_per_row);
+        quantize_row_q5_K_reference(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
-        for (int row = 0; row < nrow; ++row) {
+        for (int64_t row = 0; row < nrow; ++row) {
             quantize_row_q5_K_impl(src, (block_q5_K*)qrow, n_per_row, quant_weights);
             src += n_per_row;
             qrow += row_size;
@@ -2843,9 +2843,9 @@ size_t quantize_q5_K(const float * restrict src, void * restrict dst, int nrow,
 
 // ====================== 6-bit (de)-quantization
 
-void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict y, int k) {
+void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     int8_t L[QK_K];
     float   scales[QK_K/16];
@@ -2925,9 +2925,9 @@ void quantize_row_q6_K_reference(const float * restrict x, block_q6_K * restrict
     }
 }
 
-void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
 
@@ -2972,19 +2972,19 @@ void dequantize_row_q6_K(const block_q6_K * restrict x, float * restrict y, int
     }
 }
 
-void quantize_row_q6_K(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_q6_K(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_q6_K * restrict y = vy;
     quantize_row_q6_K_reference(x, y, k);
 }
 
-static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restrict y, int64_t n_per_row, const float * quant_weights) {
 #if QK_K != 256
     (void)quant_weights;
     quantize_row_q6_K_reference(x, y, n_per_row);
 #else
     assert(n_per_row % QK_K == 0);
-    const int nb = n_per_row / QK_K;
+    const int64_t nb = n_per_row / QK_K;
 
     int8_t L[QK_K];
     float   scales[QK_K/16];
@@ -3067,14 +3067,14 @@ static void quantize_row_q6_K_impl(const float * restrict x, block_q6_K * restri
 #endif
 }
 
-size_t quantize_q6_K(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q6_K(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     size_t row_size = ggml_row_size(GGML_TYPE_Q6_K, n_per_row);
     if (!quant_weights) {
-        quantize_row_q6_K_reference(src, dst, nrow*n_per_row);
+        quantize_row_q6_K_reference(src, dst, (int64_t)nrow*n_per_row);
     }
     else {
         char * qrow = (char *)dst;
-        for (int row = 0; row < nrow; ++row) {
+        for (int64_t row = 0; row < nrow; ++row) {
             quantize_row_q6_K_impl(src, (block_q6_K*)qrow, n_per_row, quant_weights);
             src += n_per_row;
             qrow += row_size;
@@ -3083,7 +3083,7 @@ size_t quantize_q6_K(const float * restrict src, void * restrict dst, int nrow,
     return nrow * row_size;
 }
 
-static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restrict y, int64_t n_per_row, const float * quant_weights) {
     static_assert(QK4_0 == 32, "QK4_0 must be 32");
 
     if (!quant_weights) {
@@ -3098,7 +3098,7 @@ static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restri
     for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
     float sigma2 = sum_x2/n_per_row;
 
-    const int nb = n_per_row/QK4_0;
+    const int64_t nb = n_per_row/QK4_0;
     for (int ib = 0; ib < nb; ++ib) {
         const float * xb = x + QK4_0 * ib;
         const float * qw = quant_weights + QK4_0 * ib;
@@ -3111,14 +3111,14 @@ static void quantize_row_q4_0_impl(const float * restrict x, block_q4_0 * restri
     }
 }
 
-size_t quantize_q4_0(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q4_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q4_0_reference(src, dst, nrow*n_per_row);
+        quantize_row_q4_0_reference(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q4_0, n_per_row);
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_q4_0_impl(src, (block_q4_0*)qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += row_size;
@@ -3126,7 +3126,7 @@ size_t quantize_q4_0(const float * restrict src, void * restrict dst, int nrow,
     return nrow * row_size;
 }
 
-static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restrict y, int64_t n_per_row, const float * quant_weights) {
     static_assert(QK4_1 == 32, "QK4_1 must be 32");
 
     if (!quant_weights) {
@@ -3141,7 +3141,7 @@ static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restri
     for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
     float sigma2 = sum_x2/n_per_row;
 
-    const int nb = n_per_row/QK4_1;
+    const int64_t nb = n_per_row/QK4_1;
     for (int ib = 0; ib < nb; ++ib) {
         const float * xb = x + QK4_1 * ib;
         const float * qw = quant_weights + QK4_1 * ib;
@@ -3156,14 +3156,14 @@ static void quantize_row_q4_1_impl(const float * restrict x, block_q4_1 * restri
     }
 }
 
-size_t quantize_q4_1(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q4_1(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q4_1_reference(src, dst, nrow*n_per_row);
+        quantize_row_q4_1_reference(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q4_1, n_per_row);
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_q4_1_impl(src, (block_q4_1*)qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += row_size;
@@ -3171,7 +3171,7 @@ size_t quantize_q4_1(const float * restrict src, void * restrict dst, int nrow,
     return nrow * row_size;
 }
 
-static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restrict y, int64_t n_per_row, const float * quant_weights) {
     static_assert(QK5_0 == 32, "QK5_0 must be 32");
 
     if (!quant_weights) {
@@ -3186,7 +3186,7 @@ static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restri
     for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
     float sigma2 = sum_x2/n_per_row;
 
-    const int nb = n_per_row/QK5_0;
+    const int64_t nb = n_per_row/QK5_0;
     for (int ib = 0; ib < nb; ++ib) {
         const float * xb = x + QK5_0 * ib;
         const float * qw = quant_weights + QK5_0 * ib;
@@ -3210,14 +3210,14 @@ static void quantize_row_q5_0_impl(const float * restrict x, block_q5_0 * restri
     }
 }
 
-size_t quantize_q5_0(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q5_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q5_0_reference(src, dst, nrow*n_per_row);
+        quantize_row_q5_0_reference(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q5_0, n_per_row);
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_q5_0_impl(src, (block_q5_0*)qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += row_size;
@@ -3225,7 +3225,7 @@ size_t quantize_q5_0(const float * restrict src, void * restrict dst, int nrow,
     return nrow * row_size;
 }
 
-static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restrict y, int n_per_row, const float * quant_weights) {
+static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restrict y, int64_t n_per_row, const float * quant_weights) {
     static_assert(QK5_1 == 32, "QK5_1 must be 32");
 
     if (!quant_weights) {
@@ -3240,7 +3240,7 @@ static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restri
     for (int j = 0; j < n_per_row; ++j) sum_x2 += x[j]*x[j];
     float sigma2 = sum_x2/n_per_row;
 
-    const int nb = n_per_row/QK5_1;
+    const int64_t nb = n_per_row/QK5_1;
     for (int ib = 0; ib < nb; ++ib) {
         const float * xb = x + QK5_1 * ib;
         const float * qw = quant_weights + QK5_1 * ib;
@@ -3263,14 +3263,14 @@ static void quantize_row_q5_1_impl(const float * restrict x, block_q5_1 * restri
     }
 }
 
-size_t quantize_q5_1(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q5_1(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     if (!quant_weights) {
-        quantize_row_q5_1_reference(src, dst, nrow*n_per_row);
+        quantize_row_q5_1_reference(src, dst, (int64_t)nrow*n_per_row);
         return nrow * ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
     }
     size_t row_size = ggml_row_size(GGML_TYPE_Q5_1, n_per_row);
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_q5_1_impl(src, (block_q5_1*)qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += row_size;
@@ -3278,18 +3278,18 @@ size_t quantize_q5_1(const float * restrict src, void * restrict dst, int nrow,
     return nrow * row_size;
 }
 
-size_t quantize_q8_0(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_q8_0(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     (void)quant_weights; // not used
     const size_t row_size = ggml_row_size(GGML_TYPE_Q8_0, n_per_row);
-    quantize_row_q8_0_reference(src, dst, nrow*n_per_row);
+    quantize_row_q8_0_reference(src, dst, (int64_t)nrow*n_per_row);
     return nrow * row_size;
 }
 
 // ====================== "True" 2-bit (de)-quantization
 
-void dequantize_row_iq2_xxs(const block_iq2_xxs * restrict x, float * restrict y, int k) {
+void dequantize_row_iq2_xxs(const block_iq2_xxs * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     uint32_t aux32[2];
     const uint8_t * aux8 = (const uint8_t *)aux32;
@@ -3315,9 +3315,9 @@ void dequantize_row_iq2_xxs(const block_iq2_xxs * restrict x, float * restrict y
 
 // ====================== 2.3125 bpw (de)-quantization
 
-void dequantize_row_iq2_xs(const block_iq2_xs * restrict x, float * restrict y, int k) {
+void dequantize_row_iq2_xs(const block_iq2_xs * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     float db[2];
 
@@ -3342,9 +3342,9 @@ void dequantize_row_iq2_xs(const block_iq2_xs * restrict x, float * restrict y,
 
 // ====================== 2.5625 bpw (de)-quantization
 
-void dequantize_row_iq2_s(const block_iq2_s * restrict x, float * restrict y, int k) {
+void dequantize_row_iq2_s(const block_iq2_s * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     float db[2];
 
@@ -3374,9 +3374,9 @@ void dequantize_row_iq2_s(const block_iq2_s * restrict x, float * restrict y, in
 
 // ====================== 3.0625 bpw (de)-quantization
 
-void dequantize_row_iq3_xxs(const block_iq3_xxs * restrict x, float * restrict y, int k) {
+void dequantize_row_iq3_xxs(const block_iq3_xxs * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     uint32_t aux32;
 
@@ -3406,9 +3406,9 @@ void dequantize_row_iq3_xxs(const block_iq3_xxs * restrict x, float * restrict y
 
 // ====================== 3.3125 bpw (de)-quantization
 
-void dequantize_row_iq3_s(const block_iq3_s * restrict x, float * restrict y, int k) {
+void dequantize_row_iq3_s(const block_iq3_s * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
 
@@ -3449,9 +3449,9 @@ void dequantize_row_iq3_s(const block_iq3_s * restrict x, float * restrict y, in
 
 // ====================== 1.5625 bpw (de)-quantization
 
-void dequantize_row_iq1_s(const block_iq1_s * restrict x, float * restrict y, int k) {
+void dequantize_row_iq1_s(const block_iq1_s * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
 
@@ -3474,9 +3474,9 @@ void dequantize_row_iq1_s(const block_iq1_s * restrict x, float * restrict y, in
     }
 }
 
-void dequantize_row_iq1_m(const block_iq1_m * restrict x, float * restrict y, int k) {
+void dequantize_row_iq1_m(const block_iq1_m * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     float delta[4];
     uint16_t idx[4];
@@ -3535,9 +3535,9 @@ void dequantize_row_iq1_m(const block_iq1_m * restrict x, float * restrict y, in
 
 static const int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
 
-void dequantize_row_iq4_nl(const block_iq4_nl * restrict x, float * restrict y, int k) {
+void dequantize_row_iq4_nl(const block_iq4_nl * restrict x, float * restrict y, int64_t k) {
     assert(k % QK4_NL == 0);
-    const int nb = k / QK4_NL;
+    const int64_t nb = k / QK4_NL;
 
     for (int i = 0; i < nb; i++) {
 
@@ -3553,12 +3553,12 @@ void dequantize_row_iq4_nl(const block_iq4_nl * restrict x, float * restrict y,
     }
 }
 
-void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y, int k) {
+void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
 #if QK_K == 64
     dequantize_row_iq4_nl((const block_iq4_nl *)x, y, k);
 #else
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
 
@@ -3582,9 +3582,9 @@ void dequantize_row_iq4_xs(const block_iq4_xs * restrict x, float * restrict y,
 
 //===================================== Q8_K ==============================================
 
-void quantize_row_q8_K_reference(const float * restrict x, block_q8_K * restrict y, int k) {
+void quantize_row_q8_K_reference(const float * restrict x, block_q8_K * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
 
@@ -3621,9 +3621,9 @@ void quantize_row_q8_K_reference(const float * restrict x, block_q8_K * restrict
     }
 }
 
-void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int k) {
+void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int64_t k) {
     assert(k % QK_K == 0);
-    const int nb = k / QK_K;
+    const int64_t nb = k / QK_K;
 
     for (int i = 0; i < nb; i++) {
         for (int j = 0; j < QK_K; ++j) {
@@ -3632,7 +3632,7 @@ void dequantize_row_q8_K(const block_q8_K * restrict x, float * restrict y, int
     }
 }
 
-void quantize_row_q8_K(const float * restrict x, void * restrict y, int k) {
+void quantize_row_q8_K(const float * restrict x, void * restrict y, int64_t k) {
     quantize_row_q8_K_reference(x, y, k);
 }
 
@@ -10648,7 +10648,7 @@ static int iq2_find_best_neighbour(const uint16_t * restrict neighbours, const u
     return grid_index;
 }
 
-static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict vy, int n, const float * restrict quant_weights) {
+static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights) {
 
     const int gindex = iq2_data_index(GGML_TYPE_IQ2_XXS);
 
@@ -10664,7 +10664,7 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
 
     const int kMaxQ = 3;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     block_iq2_xxs * y = vy;
 
@@ -10821,7 +10821,7 @@ static void quantize_row_iq2_xxs_impl(const float * restrict x, void * restrict
     }
 }
 
-static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict vy, int n, const float * restrict quant_weights) {
+static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights) {
 
     const int gindex = iq2_data_index(GGML_TYPE_IQ2_XS);
 
@@ -10837,7 +10837,7 @@ static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict v
 
     const int kMaxQ = 3;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     block_iq2_xs * y = vy;
 
@@ -11001,11 +11001,11 @@ static void quantize_row_iq2_xs_impl(const float * restrict x, void * restrict v
     }
 }
 
-size_t quantize_iq2_xxs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq2_xxs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq2_xxs_impl(src, qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += nblock*sizeof(block_iq2_xxs);
@@ -11013,11 +11013,11 @@ size_t quantize_iq2_xxs(const float * restrict src, void * restrict dst, int nro
     return nrow * nblock * sizeof(block_iq2_xxs);
 }
 
-size_t quantize_iq2_xs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq2_xs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq2_xs_impl(src, qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += nblock*sizeof(block_iq2_xs);
@@ -11242,7 +11242,7 @@ static int iq3_find_best_neighbour(const uint16_t * restrict neighbours, const u
     return grid_index;
 }
 
-static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, void * restrict vy, int n,
+static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, void * restrict vy, int64_t n,
         const float * restrict quant_weights) {
 
     const int gindex = iq3_data_index(grid_size);
@@ -11259,7 +11259,7 @@ static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, v
 
     const int kMaxQ = 8;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     ggml_fp16_t * dh;
     uint8_t * qs;
@@ -11455,11 +11455,11 @@ static void quantize_row_iq3_xxs_impl(int grid_size, const float * restrict x, v
     }
 }
 
-size_t quantize_iq3_xxs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq3_xxs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq3_xxs_impl(256, src, qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += nblock*sizeof(block_iq3_xxs);
@@ -11467,13 +11467,13 @@ size_t quantize_iq3_xxs(const float * restrict src, void * restrict dst, int nro
     return nrow * nblock * sizeof(block_iq3_xxs);
 }
 
-void quantize_row_iq3_xxs(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_iq3_xxs(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq3_xxs * restrict y = vy;
     quantize_row_iq3_xxs_reference(x, y, k);
 }
 
-void quantize_row_iq3_xxs_reference(const float * restrict x, block_iq3_xxs * restrict y, int k) {
+void quantize_row_iq3_xxs_reference(const float * restrict x, block_iq3_xxs * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_row_iq3_xxs_impl(256, x, y, k, NULL);
 }
@@ -11504,7 +11504,7 @@ static void quantize_row_iq3_s_impl(int block_size, const float * restrict x, vo
 
     const int kMaxQ = 8;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     block_iq3_s * y = vy;
 
@@ -11661,9 +11661,9 @@ static void quantize_row_iq3_s_impl(int block_size, const float * restrict x, vo
 }
 
 #define IQ3S_BLOCK_SIZE 32
-size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     float scales[QK_K/IQ3S_BLOCK_SIZE];
     float weight[IQ3S_BLOCK_SIZE];
     float xval[IQ3S_BLOCK_SIZE];
@@ -11674,7 +11674,7 @@ size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int nrow,
     bool   is_on_grid_aux[IQ3S_BLOCK_SIZE/4];
     uint8_t block_signs[IQ3S_BLOCK_SIZE/8];
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq3_s_impl(IQ3S_BLOCK_SIZE, src, qrow, n_per_row, quant_weights,
                 scales, weight, xval, L, Laux, waux, is_on_grid, is_on_grid_aux, block_signs);
         src += n_per_row;
@@ -11683,13 +11683,13 @@ size_t quantize_iq3_s(const float * restrict src, void * restrict dst, int nrow,
     return nrow * nblock * sizeof(block_iq3_s);
 }
 
-void quantize_row_iq3_s(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_iq3_s(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq3_s * restrict y = vy;
     quantize_row_iq3_s_reference(x, y, k);
 }
 
-void quantize_row_iq3_s_reference(const float * restrict x, block_iq3_s * restrict y, int k) {
+void quantize_row_iq3_s_reference(const float * restrict x, block_iq3_s * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_iq3_s(x, y, 1, k, NULL);
 }
@@ -11822,7 +11822,7 @@ static int iq1_sort_helper(const void * left, const void * right) {
 
 #define IQ1S_BLOCK_SIZE 32
 #define IQ1M_BLOCK_SIZE 16
-static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy, int n, const float * restrict quant_weights,
+static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights,
         float    * scales,
         float    * weight,
         float    * sumx,
@@ -11846,7 +11846,7 @@ static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy
 
     block_iq1_s * y = vy;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     const int block_size = IQ1S_BLOCK_SIZE;
 
@@ -11980,7 +11980,7 @@ static void quantize_row_iq1_s_impl(const float * restrict x, void * restrict vy
     }
 }
 
-size_t quantize_iq1_s(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq1_s(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
     float  scales[QK_K/IQ1S_BLOCK_SIZE];
     float  weight[IQ1S_BLOCK_SIZE];
@@ -11990,9 +11990,9 @@ size_t quantize_iq1_s(const float * restrict src, void * restrict dst, int nrow,
     float  pairs[2*IQ1S_BLOCK_SIZE];
     uint16_t index[IQ1S_BLOCK_SIZE/8];
     int8_t shifts[QK_K/IQ1S_BLOCK_SIZE];
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq1_s_impl(src, qrow, n_per_row, quant_weights, scales, weight, sumx, sumw, pairs, L, index, shifts);
         src += n_per_row;
         qrow += nblock*sizeof(block_iq1_s);
@@ -12000,7 +12000,7 @@ size_t quantize_iq1_s(const float * restrict src, void * restrict dst, int nrow,
     return nrow * nblock * sizeof(block_iq1_s);
 }
 
-static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy, int n, const float * restrict quant_weights,
+static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights,
         float    * scales,
         float    * weight,
         float    * pairs,
@@ -12022,7 +12022,7 @@ static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy
 
     block_iq1_m * y = vy;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     const int block_size = IQ1M_BLOCK_SIZE;
 
@@ -12265,7 +12265,7 @@ static void quantize_row_iq1_m_impl(const float * restrict x, void * restrict vy
     }
 }
 
-size_t quantize_iq1_m(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq1_m(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
     float  scales[QK_K/IQ1M_BLOCK_SIZE];
     float  weight[IQ1M_BLOCK_SIZE];
@@ -12273,9 +12273,9 @@ size_t quantize_iq1_m(const float * restrict src, void * restrict dst, int nrow,
     float  pairs[2*IQ1M_BLOCK_SIZE];
     uint16_t index[IQ1M_BLOCK_SIZE/8];
     int8_t shifts[QK_K/IQ1M_BLOCK_SIZE];
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq1_m_impl(src, qrow, n_per_row, quant_weights, scales, weight, pairs, L, index, shifts);
         src += n_per_row;
         qrow += nblock*sizeof(block_iq1_m);
@@ -12407,16 +12407,16 @@ static void quantize_row_iq4_nl_impl(const int super_block_size, const int block
     }
 }
 
-size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK4_NL == 0);
-    int nblock = n_per_row/QK4_NL;
+    int64_t nblock = n_per_row/QK4_NL;
     char * qrow = (char *)dst;
     uint8_t L[QK4_NL];
     float weight[QK4_NL];
     uint16_t unused_h;
     uint8_t * unused_l = NULL;
     float scale;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         block_iq4_nl * iq4 = (block_iq4_nl *)qrow;
         for (int ibl = 0; ibl < nblock; ++ibl) {
             const float * qw = quant_weights ? quant_weights + QK4_NL*ibl : NULL;
@@ -12429,9 +12429,9 @@ size_t quantize_iq4_nl(const float * restrict src, void * restrict dst, int nrow
     return nrow * nblock * sizeof(block_iq4_nl);
 }
 
-void quantize_row_iq4_nl(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_iq4_nl(const float * restrict x, void * restrict vy, int64_t k) {
     GGML_ASSERT(k%QK4_NL == 0);
-    int nblock = k/QK4_NL;
+    int64_t nblock = k/QK4_NL;
     uint8_t L[QK4_NL];
     float weight[QK4_NL];
     uint16_t unused_h;
@@ -12444,22 +12444,22 @@ void quantize_row_iq4_nl(const float * restrict x, void * restrict vy, int k) {
     }
 }
 
-void quantize_row_iq4_nl_reference(const float * restrict x, block_iq4_nl * restrict y, int k) {
+void quantize_row_iq4_nl_reference(const float * restrict x, block_iq4_nl * restrict y, int64_t k) {
     assert(k % QK4_NL == 0);
     quantize_row_iq4_nl(x, y, k);
 }
 
-size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
 #if QK_K == 64
     return quantize_iq4_nl(src, dst, nrow, n_per_row, quant_weights);
 #else
     GGML_ASSERT(n_per_row%QK_K == 0);
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
     uint8_t L[QK_K];
     float weight[32];
     float scales[QK_K/32];
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         block_iq4_xs * iq4 = (block_iq4_xs *)qrow;
         for (int ibl = 0; ibl < nblock; ++ibl) {
             const float * qw = quant_weights ? quant_weights + QK_K*ibl : NULL;
@@ -12473,20 +12473,20 @@ size_t quantize_iq4_xs(const float * restrict src, void * restrict dst, int nrow
 #endif
 }
 
-void quantize_row_iq4_xs(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_iq4_xs(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq4_xs * restrict y = vy;
     quantize_row_iq4_xs_reference(x, y, k);
 }
 
-void quantize_row_iq4_xs_reference(const float * restrict x, block_iq4_xs * restrict y, int k) {
+void quantize_row_iq4_xs_reference(const float * restrict x, block_iq4_xs * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_iq4_xs(x, y, 1, k, NULL);
 }
 
 // =============================== 2.5625 bpw
 
-static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy, int n, const float * restrict quant_weights) {
+static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy, int64_t n, const float * restrict quant_weights) {
 
     const int gindex = iq2_data_index(GGML_TYPE_IQ2_S);
 
@@ -12501,7 +12501,7 @@ static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy
 
     const int kMaxQ = 3;
 
-    const int nbl = n/QK_K;
+    const int64_t nbl = n/QK_K;
 
     block_iq2_s * y = vy;
 
@@ -12654,11 +12654,11 @@ static void quantize_row_iq2_s_impl(const float * restrict x, void * restrict vy
     }
 }
 
-size_t quantize_iq2_s(const float * restrict src, void * restrict dst, int nrow, int n_per_row, const float * quant_weights) {
+size_t quantize_iq2_s(const float * restrict src, void * restrict dst, int64_t nrow, int64_t n_per_row, const float * quant_weights) {
     GGML_ASSERT(n_per_row%QK_K == 0);
-    int nblock = n_per_row/QK_K;
+    int64_t nblock = n_per_row/QK_K;
     char * qrow = (char *)dst;
-    for (int row = 0; row < nrow; ++row) {
+    for (int64_t row = 0; row < nrow; ++row) {
         quantize_row_iq2_s_impl(src, qrow, n_per_row, quant_weights);
         src += n_per_row;
         qrow += nblock*sizeof(block_iq2_s);
@@ -12666,12 +12666,12 @@ size_t quantize_iq2_s(const float * restrict src, void * restrict dst, int nrow,
     return nrow * nblock * sizeof(block_iq2_s);
 }
 
-void quantize_row_iq2_s_reference(const float * restrict x, block_iq2_s * restrict y, int k) {
+void quantize_row_iq2_s_reference(const float * restrict x, block_iq2_s * restrict y, int64_t k) {
     assert(k % QK_K == 0);
     quantize_iq2_s(x, y, 1, k, NULL);
 }
 
-void quantize_row_iq2_s(const float * restrict x, void * restrict vy, int k) {
+void quantize_row_iq2_s(const float * restrict x, void * restrict vy, int64_t k) {
     assert(k % QK_K == 0);
     block_iq2_s * restrict y = vy;
     quantize_row_iq2_s_reference(x, y, k);
diff --git a/ggml-quants.h b/ggml-quants.h
index ac1091c3d..4d436a8f0 100644
--- a/ggml-quants.h
+++ b/ggml-quants.h
@@ -12,70 +12,70 @@ extern "C" {
 #endif
 
 // Quantization
-void quantize_row_q4_0_reference(const float * GGML_RESTRICT x, block_q4_0 * GGML_RESTRICT y, int k);
-void quantize_row_q4_1_reference(const float * GGML_RESTRICT x, block_q4_1 * GGML_RESTRICT y, int k);
-void quantize_row_q5_0_reference(const float * GGML_RESTRICT x, block_q5_0 * GGML_RESTRICT y, int k);
-void quantize_row_q5_1_reference(const float * GGML_RESTRICT x, block_q5_1 * GGML_RESTRICT y, int k);
-void quantize_row_q8_0_reference(const float * GGML_RESTRICT x, block_q8_0 * GGML_RESTRICT y, int k);
-void quantize_row_q8_1_reference(const float * GGML_RESTRICT x, block_q8_1 * GGML_RESTRICT y, int k);
+void quantize_row_q4_0_reference(const float * GGML_RESTRICT x, block_q4_0 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_1_reference(const float * GGML_RESTRICT x, block_q4_1 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_0_reference(const float * GGML_RESTRICT x, block_q5_0 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_1_reference(const float * GGML_RESTRICT x, block_q5_1 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_0_reference(const float * GGML_RESTRICT x, block_q8_0 * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_1_reference(const float * GGML_RESTRICT x, block_q8_1 * GGML_RESTRICT y, int64_t k);
 
-void quantize_row_q2_K_reference(const float * GGML_RESTRICT x, block_q2_K * GGML_RESTRICT y, int k);
-void quantize_row_q3_K_reference(const float * GGML_RESTRICT x, block_q3_K * GGML_RESTRICT y, int k);
-void quantize_row_q4_K_reference(const float * GGML_RESTRICT x, block_q4_K * GGML_RESTRICT y, int k);
-void quantize_row_q5_K_reference(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int k);
-void quantize_row_q6_K_reference(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int k);
-void quantize_row_q8_K_reference(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int k);
+void quantize_row_q2_K_reference(const float * GGML_RESTRICT x, block_q2_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q3_K_reference(const float * GGML_RESTRICT x, block_q3_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_K_reference(const float * GGML_RESTRICT x, block_q4_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_K_reference(const float * GGML_RESTRICT x, block_q5_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q6_K_reference(const float * GGML_RESTRICT x, block_q6_K * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_K_reference(const float * GGML_RESTRICT x, block_q8_K * GGML_RESTRICT y, int64_t k);
 
-void quantize_row_iq3_xxs_reference(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int k);
-void quantize_row_iq4_nl_reference (const float * GGML_RESTRICT x, block_iq4_nl  * GGML_RESTRICT y, int k);
-void quantize_row_iq4_xs_reference (const float * GGML_RESTRICT x, block_iq4_xs  * GGML_RESTRICT y, int k);
-void quantize_row_iq3_s_reference  (const float * GGML_RESTRICT x, block_iq3_s   * GGML_RESTRICT y, int k);
-void quantize_row_iq2_s_reference  (const float * GGML_RESTRICT x, block_iq2_s   * GGML_RESTRICT y, int k);
+void quantize_row_iq3_xxs_reference(const float * GGML_RESTRICT x, block_iq3_xxs * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq4_nl_reference (const float * GGML_RESTRICT x, block_iq4_nl  * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq4_xs_reference (const float * GGML_RESTRICT x, block_iq4_xs  * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq3_s_reference  (const float * GGML_RESTRICT x, block_iq3_s   * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq2_s_reference  (const float * GGML_RESTRICT x, block_iq2_s   * GGML_RESTRICT y, int64_t k);
 
-void quantize_row_q4_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q4_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q5_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q5_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
+void quantize_row_q4_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 
-void quantize_row_q2_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q3_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q4_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q5_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q6_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
+void quantize_row_q2_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q3_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q4_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q5_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q6_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 
-void quantize_row_iq3_xxs(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_iq4_nl (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_iq4_xs (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_iq3_s  (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
-void quantize_row_iq2_s  (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int k);
+void quantize_row_iq3_xxs(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq4_nl (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq4_xs (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq3_s  (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
+void quantize_row_iq2_s  (const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k);
 
 // Dequantization
-void dequantize_row_q4_0(const block_q4_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q4_1(const block_q4_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q5_0(const block_q5_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q5_1(const block_q5_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q8_0(const block_q8_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-//void dequantize_row_q8_1(const block_q8_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
+void dequantize_row_q4_0(const block_q4_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q4_1(const block_q4_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q5_0(const block_q5_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q5_1(const block_q5_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q8_0(const block_q8_0 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+//void dequantize_row_q8_1(const block_q8_1 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
 
-void dequantize_row_q2_K(const block_q2_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q3_K(const block_q3_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q4_K(const block_q4_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q5_K(const block_q5_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q6_K(const block_q6_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_q8_K(const block_q8_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
+void dequantize_row_q2_K(const block_q2_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q3_K(const block_q3_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q4_K(const block_q4_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q5_K(const block_q5_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q6_K(const block_q6_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_q8_K(const block_q8_K * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
 
-void dequantize_row_iq2_xxs(const block_iq2_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq2_xs (const block_iq2_xs  * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq2_s  (const block_iq2_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq3_xxs(const block_iq3_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq1_s  (const block_iq1_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq1_m  (const block_iq1_m   * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq4_nl (const block_iq4_nl  * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq4_xs (const block_iq4_xs  * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-void dequantize_row_iq3_s  (const block_iq3_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
+void dequantize_row_iq2_xxs(const block_iq2_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq2_xs (const block_iq2_xs  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq2_s  (const block_iq2_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq3_xxs(const block_iq3_xxs * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq1_s  (const block_iq1_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq1_m  (const block_iq1_m   * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq4_nl (const block_iq4_nl  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq4_xs (const block_iq4_xs  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+void dequantize_row_iq3_s  (const block_iq3_s   * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
 
 // Dot product
 void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
@@ -101,26 +101,26 @@ void ggml_vec_dot_iq4_xs_q8_K (int n, float * GGML_RESTRICT s, size_t bs, const
 void ggml_vec_dot_iq3_s_q8_K  (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc);
 
 // Quantization utilizing an importance matrix (a.k.a. "Activation aWare Quantization")
-size_t quantize_iq2_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq2_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq2_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq3_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq1_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq1_m  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq4_nl (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq4_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_iq3_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_iq2_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq2_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq2_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq3_xxs(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq1_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq1_m  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq4_nl (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq4_xs (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_iq3_s  (const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
 
-size_t quantize_q2_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q3_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q4_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q5_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q6_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q4_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q4_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q5_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q5_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
-size_t quantize_q8_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int nrows, int n_per_row, const float * imatrix);
+size_t quantize_q2_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q3_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q5_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q6_K(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q4_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q5_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q5_1(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
+size_t quantize_q8_0(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix);
 
 void iq2xs_init_impl(enum ggml_type type);
 void iq2xs_free_impl(enum ggml_type type);
diff --git a/ggml.c b/ggml.c
index c9b0a6a0e..793b67f4c 100644
--- a/ggml.c
+++ b/ggml.c
@@ -338,14 +338,14 @@ ggml_fp16_t ggml_fp32_to_fp16(float x) {
     return GGML_FP32_TO_FP16(x);
 }
 
-void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int n) {
-    for (int i = 0; i < n; i++) {
+void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int64_t n) {
+    for (int64_t i = 0; i < n; i++) {
         y[i] = GGML_FP16_TO_FP32(x[i]);
     }
 }
 
-void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int n) {
-    int i = 0;
+void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int64_t n) {
+    int64_t i = 0;
 #if defined(__F16C__)
     for (; i + 7 < n; i += 8) {
         __m256 x_vec = _mm256_loadu_ps(x + i);
@@ -20331,11 +20331,11 @@ size_t ggml_quantize_chunk(
         enum ggml_type   type,
            const float * src,
                   void * dst,
-                   int   start,
-                   int   nrows,
-                   int   n_per_row,
+               int64_t   start,
+               int64_t   nrows,
+               int64_t   n_per_row,
            const float * imatrix) {
-    const int n = nrows * n_per_row;
+    const int64_t n = (int64_t) nrows * n_per_row;
 
     if (ggml_quantize_requires_imatrix(type)) {
         GGML_ASSERT(imatrix != NULL);
diff --git a/ggml.h b/ggml.h
index 5cef45c0b..abe3767f2 100644
--- a/ggml.h
+++ b/ggml.h
@@ -332,8 +332,8 @@ extern "C" {
     GGML_API float       ggml_fp16_to_fp32(ggml_fp16_t x);
     GGML_API ggml_fp16_t ggml_fp32_to_fp16(float x);
 
-    GGML_API void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int n);
-    GGML_API void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int n);
+    GGML_API void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int64_t n);
+    GGML_API void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int64_t n);
 
     struct ggml_object;
     struct ggml_context;
@@ -2210,9 +2210,9 @@ extern "C" {
             enum ggml_type   type,
                const float * src,
                       void * dst,
-                       int   start,
-                       int   nrows,
-                       int   n_per_row,
+                   int64_t   start,
+                   int64_t   nrows,
+                   int64_t   n_per_row,
                const float * imatrix);
 
     //
@@ -2377,8 +2377,8 @@ extern "C" {
 #else
 #define GGML_RESTRICT restrict
 #endif
-    typedef void (*ggml_to_float_t)  (const void  * GGML_RESTRICT x, float * GGML_RESTRICT y, int k);
-    typedef void (*ggml_from_float_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int k);
+    typedef void (*ggml_to_float_t)  (const void  * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k);
+    typedef void (*ggml_from_float_t)(const float * GGML_RESTRICT x, void  * GGML_RESTRICT y, int64_t k);
     typedef void (*ggml_vec_dot_t)   (int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT x, size_t bx,
                                       const void * GGML_RESTRICT y, size_t by, int nrc);
 
diff --git a/gguf-py/gguf/constants.py b/gguf-py/gguf/constants.py
index c44d8abeb..a6454a10e 100644
--- a/gguf-py/gguf/constants.py
+++ b/gguf-py/gguf/constants.py
@@ -639,6 +639,8 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
         MODEL_TENSOR.FFN_GATE,
         MODEL_TENSOR.FFN_DOWN,
         MODEL_TENSOR.FFN_UP,
+        MODEL_TENSOR.ATTN_K_NORM,
+        MODEL_TENSOR.ATTN_Q_NORM,
     ],
     # TODO
 }
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py
index 345b1b0c7..4f02d298e 100644
--- a/gguf-py/gguf/tensor_mapping.py
+++ b/gguf-py/gguf/tensor_mapping.py
@@ -285,12 +285,14 @@ class TensorNameMap:
         MODEL_TENSOR.ATTN_Q_NORM: (
             "language_model.encoder.layers.{bid}.self_attention.q_layernorm",
             "model.layers.{bid}.self_attn.q_layernorm",                       # persimmon
+            "model.layers.{bid}.self_attn.q_norm",                            # cohere
             "transformer.blocks.{bid}.attn.q_ln",                             # sea-lion
         ),
 
         MODEL_TENSOR.ATTN_K_NORM: (
             "language_model.encoder.layers.{bid}.self_attention.k_layernorm",
             "model.layers.{bid}.self_attn.k_layernorm",                       # persimmon
+            "model.layers.{bid}.self_attn.k_norm",                            # cohere
             "transformer.blocks.{bid}.attn.k_ln",                             # sea-lion
         ),
 
diff --git a/llama.cpp b/llama.cpp
index b16ddc64c..6a090d1bb 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -926,6 +926,8 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
             { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
             { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
             { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_ATTN_Q_NORM,     "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K_NORM,     "blk.%d.attn_k_norm" },
         },
     },
     {
@@ -5406,6 +5408,11 @@ static bool llm_load_tensors(
 
                         layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
 
+                        if (n_layer >= 64){
+                            layer.attn_q_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head});
+                            layer.attn_k_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_K_NORM, "weight", i), {hparams.n_embd_head_k, hparams.n_head_kv});
+                        }
+
                         layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q,   "weight", i), {n_embd, n_embd});
                         layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K,   "weight", i), {n_embd, n_embd_gqa});
                         layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V,   "weight", i), {n_embd, n_embd_gqa});
@@ -9454,6 +9461,31 @@ struct llm_build_context {
                     cb(Vcur, "Vcur", il);
                 }
 
+                if (model.layers[il].attn_q_norm) {
+                    Qcur = ggml_view_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens,
+                                ggml_element_size(Qcur) * n_embd_head,
+                                ggml_element_size(Qcur) * n_embd_head * n_head,
+                                0);
+                    cb(Qcur, "Qcur", il);
+                    Kcur = ggml_view_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens,
+                                ggml_element_size(Kcur) * n_embd_head,
+                                ggml_element_size(Kcur) * n_embd_head * n_head_kv,
+                                0);
+                    cb(Kcur, "Kcur", il);
+
+                    Qcur = llm_build_norm(ctx0, Qcur, hparams,
+                                model.layers[il].attn_q_norm,
+                                NULL,
+                                LLM_NORM, cb, il);
+                    cb(Qcur, "Qcur", il);
+
+                    Kcur = llm_build_norm(ctx0, Kcur, hparams,
+                            model.layers[il].attn_k_norm,
+                            NULL,
+                            LLM_NORM, cb, il);
+                    cb(Kcur, "Kcur", il);
+                }
+
                 Qcur = ggml_rope_custom(
                     ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens), inp_pos,
                     n_rot, rope_type, 0, n_orig_ctx, freq_base, freq_scale,
@@ -13323,9 +13355,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
     return new_type;
 }
 
-static size_t llama_tensor_quantize_internal(enum ggml_type new_type, const float * f32_data, void * new_data, const int chunk_size, int nrows, int n_per_row, const float * imatrix, std::vector<std::thread> & workers, const int nthread) {
+static size_t llama_tensor_quantize_internal(enum ggml_type new_type, const float * f32_data, void * new_data, const int64_t chunk_size, int64_t nrows, int64_t n_per_row, const float * imatrix, std::vector<std::thread> & workers, const int nthread) {
     std::mutex mutex;
-    int counter = 0;
+    int64_t counter = 0;
     size_t new_size = 0;
     if (nthread < 2) {
         // single-thread
@@ -13333,11 +13365,11 @@ static size_t llama_tensor_quantize_internal(enum ggml_type new_type, const floa
     }
     auto compute = [&mutex, &counter, &new_size, new_type, f32_data, new_data, chunk_size,
             nrows, n_per_row, imatrix]() {
-        const int nrows_per_chunk = chunk_size / n_per_row;
+        const int64_t nrows_per_chunk = chunk_size / n_per_row;
         size_t local_size = 0;
         while (true) {
             std::unique_lock<std::mutex> lock(mutex);
-            int first_row = counter; counter += nrows_per_chunk;
+            int64_t first_row = counter; counter += nrows_per_chunk;
             if (first_row >= nrows) {
                 if (local_size > 0) {
                     new_size += local_size;
@@ -13345,7 +13377,7 @@ static size_t llama_tensor_quantize_internal(enum ggml_type new_type, const floa
                 break;
             }
             lock.unlock();
-            const int this_nrow = std::min(nrows - first_row, nrows_per_chunk);
+            const int64_t this_nrow = std::min(nrows - first_row, nrows_per_chunk);
             local_size += ggml_quantize_chunk(new_type, f32_data, new_data, first_row * n_per_row, this_nrow, n_per_row, imatrix);
         }
     };
@@ -13539,6 +13571,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
 
         // quantize only 2D and 3D tensors (experts)
         quantize &= (ggml_n_dims(tensor) >= 2);
+
+        // do not quantize norm tensors
+        quantize &= name.find("_norm.weight") == std::string::npos;
+
         quantize &= params->quantize_output_tensor || name != "output.weight";
         quantize &= !params->only_copy;
 
@@ -13585,7 +13621,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
             new_size = ggml_nbytes(tensor);
             LLAMA_LOG_INFO("size = %8.3f MB\n", ggml_nbytes(tensor)/1024.0/1024.0);
         } else {
-            const size_t nelements = ggml_nelements(tensor);
+            const int64_t nelements = ggml_nelements(tensor);
 
             const float * imatrix = nullptr;
             if (imatrix_data) {
@@ -13637,20 +13673,20 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
             LLAMA_LOG_INFO("converting to %s .. ", ggml_type_name(new_type));
             fflush(stdout);
 
-            if (work.size() < nelements * 4) {
+            if (work.size() < (size_t)nelements * 4) {
                 work.resize(nelements * 4); // upper bound on size
             }
             new_data = work.data();
 
-            const int n_per_row = tensor->ne[0];
-            const int nrows = tensor->ne[1];
+            const int64_t n_per_row = tensor->ne[0];
+            const int64_t nrows = tensor->ne[1];
 
-            static const int min_chunk_size = 32 * 512;
-            const int chunk_size = n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row);
+            static const int64_t min_chunk_size = 32 * 512;
+            const int64_t chunk_size = n_per_row >= min_chunk_size ? n_per_row : n_per_row * ((min_chunk_size + n_per_row - 1)/n_per_row);
 
-            const int nelements_matrix = tensor->ne[0] * tensor->ne[1];
-            const int nchunk = (nelements_matrix + chunk_size - 1)/chunk_size;
-            const int nthread_use = nthread > 1 ? std::max(1, std::min(nthread, nchunk)) : 1;
+            const int64_t nelements_matrix = tensor->ne[0] * tensor->ne[1];
+            const int64_t nchunk = (nelements_matrix + chunk_size - 1)/chunk_size;
+            const int64_t nthread_use = nthread > 1 ? std::max((int64_t)1, std::min((int64_t)nthread, nchunk)) : 1;
 
             // quantize each expert separately since they have different importance matrices
             new_size = 0;

From 400d5d722d7edf7de0cf24a18c42b183c65047d2 Mon Sep 17 00:00:00 2001
From: Ed Lee <edilee@mozilla.com>
Date: Tue, 9 Apr 2024 01:31:47 -0700
Subject: [PATCH 9/9] server : detect search query to start webchat (#6554)

---
 examples/server/index.html.hpp    | 3680 +++++++++++++++--------------
 examples/server/public/index.html |    6 +-
 2 files changed, 1851 insertions(+), 1835 deletions(-)

diff --git a/examples/server/index.html.hpp b/examples/server/index.html.hpp
index 2de8a5fd2..122d3ff99 100644
--- a/examples/server/index.html.hpp
+++ b/examples/server/index.html.hpp
@@ -917,92 +917,184 @@ unsigned char index_html[] = {
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+  0x79, 0x3a, 0x20, 0x6e, 0x6f, 0x6e, 0x65, 0x3b, 0x22, 0x3e, 0x0a, 0x20,
+  0x20, 0x3c, 0x2f, 0x64, 0x69, 0x76, 0x3e, 0x0a, 0x20, 0x20, 0x3c, 0x64,
+  0x69, 0x76, 0x20, 0x69, 0x64, 0x3d, 0x22, 0x70, 0x6f, 0x72, 0x74, 0x61,
+  0x6c, 0x22, 0x3e, 0x3c, 0x2f, 0x64, 0x69, 0x76, 0x3e, 0x0a, 0x3c, 0x2f,
+  0x62, 0x6f, 0x64, 0x79, 0x3e, 0x0a, 0x0a, 0x3c, 0x2f, 0x68, 0x74, 0x6d,
+  0x6c, 0x3e, 0x0a, 0x0a
 };
-unsigned int index_html_len = 34412;
+unsigned int index_html_len = 34552;
diff --git a/examples/server/public/index.html b/examples/server/public/index.html
index c91a357c1..9fe61eb1b 100644
--- a/examples/server/public/index.html
+++ b/examples/server/public/index.html
@@ -406,7 +406,7 @@
         throw new Error("already running");
       }
       controller.value = new AbortController();
-      for await (const chunk of llama(prompt, llamaParams, { controller: controller.value, api_url: document.baseURI.replace(/\/+$/, '') })) {
+      for await (const chunk of llama(prompt, llamaParams, { controller: controller.value, api_url: location.pathname.replace(/\/+$/, '') })) {
         const data = chunk.data;
 
         if (data.stop) {
@@ -1015,6 +1015,10 @@
     }
 
     function App(props) {
+      useEffect(() => {
+        const query = new URLSearchParams(location.search).get("q");
+        if (query) chat(query);
+      }, []);
 
       return html`
         <div class="mode-${session.value.type}">