mirror of
https://github.com/LostRuins/koboldcpp.git
synced 2025-09-13 18:39:48 +00:00
not working merge
This commit is contained in:
commit
bc4ff72317
38 changed files with 886 additions and 360 deletions
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@ -1,9 +1,6 @@
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set(TARGET benchmark)
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add_executable(${TARGET} benchmark-matmult.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE llama ${CMAKE_THREAD_LIBS_INIT})
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target_link_libraries(${TARGET} PRIVATE llama build_info ${CMAKE_THREAD_LIBS_INIT})
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target_include_directories(${TARGET} PRIVATE ../../common)
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -3,6 +3,3 @@ add_executable(${TARGET} embedding.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -642,8 +642,9 @@ static struct ggml_tensor * llama_build_lora_finetune_graphs(
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const int rope_mode = 0;
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return ggml_rope_custom(ctx,
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t, KQ_pos, n_rot, rope_mode, n_ctx,
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rope_freq_base, rope_freq_scale);
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t, KQ_pos, n_rot, rope_mode, n_ctx, 0,
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rope_freq_base, rope_freq_scale, 0.0f, 0.0f, 0.0f, 0.0f
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);
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};
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set_name(tokens_input, "tokens_input");
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@ -3,6 +3,3 @@ add_executable(${TARGET} infill.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -184,8 +184,8 @@ int main(int argc, char ** argv) {
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LOG_TEE("%s: warning: scaling RoPE frequency by %g.\n", __func__, params.rope_freq_scale);
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}
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LOG_TEE("%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
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LOG_TEE("%s: built with %s for %s\n", __func__, BUILD_COMPILER, BUILD_TARGET);
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LOG_TEE("%s: build = %d (%s)\n", __func__, LLAMA_BUILD_NUMBER, LLAMA_COMMIT);
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LOG_TEE("%s: built with %s for %s\n", __func__, LLAMA_COMPILER, LLAMA_BUILD_TARGET);
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if (params.seed == LLAMA_DEFAULT_SEED) {
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params.seed = time(NULL);
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@ -3,6 +3,3 @@ add_executable(${TARGET} llama-bench.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -641,8 +641,8 @@ struct test {
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}
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};
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const std::string test::build_commit = BUILD_COMMIT;
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const int test::build_number = BUILD_NUMBER;
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const std::string test::build_commit = LLAMA_COMMIT;
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const int test::build_number = LLAMA_BUILD_NUMBER;
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const bool test::cuda = !!ggml_cpu_has_cublas();
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const bool test::opencl = !!ggml_cpu_has_clblast();
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const bool test::metal = !!ggml_cpu_has_metal();
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@ -5,9 +5,6 @@ target_link_libraries(${TARGET} PRIVATE common ggml ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if (NOT MSVC)
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target_compile_options(${TARGET} PRIVATE -Wno-cast-qual) # stb_image.h
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endif()
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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set(TARGET llava)
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@ -15,6 +12,3 @@ add_executable(${TARGET} llava.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama clip ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -3,6 +3,3 @@ add_executable(${TARGET} main.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -153,8 +153,8 @@ int main(int argc, char ** argv) {
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LOG_TEE("%s: warning: scaling RoPE frequency by %g.\n", __func__, params.rope_freq_scale);
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}
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LOG_TEE("%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
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LOG_TEE("%s: built with %s for %s\n", __func__, BUILD_COMPILER, BUILD_TARGET);
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LOG_TEE("%s: build = %d (%s)\n", __func__, LLAMA_BUILD_NUMBER, LLAMA_COMMIT);
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LOG_TEE("%s: built with %s for %s\n", __func__, LLAMA_COMPILER, LLAMA_BUILD_TARGET);
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if (params.seed == LLAMA_DEFAULT_SEED) {
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params.seed = time(NULL);
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@ -3,6 +3,3 @@ add_executable(${TARGET} parallel.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -3,6 +3,3 @@ add_executable(${TARGET} perplexity.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -1,6 +1,6 @@
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set(TARGET quantize-stats)
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add_executable(${TARGET} quantize-stats.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE llama ${CMAKE_THREAD_LIBS_INIT})
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target_link_libraries(${TARGET} PRIVATE llama build_info ${CMAKE_THREAD_LIBS_INIT})
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target_include_directories(${TARGET} PRIVATE ../../common)
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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@ -1,9 +1,6 @@
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set(TARGET quantize)
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add_executable(${TARGET} quantize.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE llama ${CMAKE_THREAD_LIBS_INIT})
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target_link_libraries(${TARGET} PRIVATE llama build_info ${CMAKE_THREAD_LIBS_INIT})
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target_include_directories(${TARGET} PRIVATE ../../common)
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -3,6 +3,3 @@ add_executable(${TARGET} save-load-state.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -11,6 +11,3 @@ if (WIN32)
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TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
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endif()
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -1755,12 +1755,18 @@ static void server_print_usage(const char *argv0, const gpt_params ¶ms,
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printf("options:\n");
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printf(" -h, --help show this help message and exit\n");
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printf(" -v, --verbose verbose output (default: %s)\n", server_verbose ? "enabled" : "disabled");
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printf(" -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
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printf(" -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
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printf(" -tb N, --threads-batch N number of threads to use during batch and prompt processing (default: same as --threads)\n");
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printf(" -c N, --ctx-size N size of the prompt context (default: %d)\n", params.n_ctx);
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printf(" -c N, --ctx-size N size of the prompt context (default: %d)\n", params.n_ctx);
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printf(" --rope-scaling {none,linear,yarn}\n");
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printf(" RoPE frequency scaling method, defaults to linear unless specified by the model\n");
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printf(" --rope-freq-base N RoPE base frequency (default: loaded from model)\n");
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printf(" --rope-freq-scale N RoPE frequency scaling factor (default: loaded from model)\n");
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printf(" -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch);
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printf(" --rope-freq-scale N RoPE frequency scaling factor, expands context by a factor of 1/N\n");
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printf(" --yarn-ext-factor N YaRN: extrapolation mix factor (default: 1.0, 0.0 = full interpolation)\n");
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printf(" --yarn-attn-factor N YaRN: scale sqrt(t) or attention magnitude (default: 1.0)\n");
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printf(" --yarn-beta-slow N YaRN: high correction dim or alpha (default: %.1f)\n", params.yarn_beta_slow);
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printf(" --yarn-beta-fast N YaRN: low correction dim or beta (default: %.1f)\n", params.yarn_beta_fast);
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printf(" -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch);
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printf(" --memory-f32 use f32 instead of f16 for memory key+value (default: disabled)\n");
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printf(" not recommended: doubles context memory required and no measurable increase in quality\n");
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if (llama_mlock_supported())
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@ -1881,6 +1887,19 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
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}
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params.n_ctx = std::stoi(argv[i]);
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}
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else if (arg == "--rope-scaling")
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{
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if (++i >= argc)
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{
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invalid_param = true;
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break;
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}
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std::string value(argv[i]);
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/**/ if (value == "none") { params.rope_scaling_type = LLAMA_ROPE_SCALING_NONE; }
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else if (value == "linear") { params.rope_scaling_type = LLAMA_ROPE_SCALING_LINEAR; }
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else if (value == "yarn") { params.rope_scaling_type = LLAMA_ROPE_SCALING_YARN; }
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else { invalid_param = true; break; }
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}
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else if (arg == "--rope-freq-base")
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{
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if (++i >= argc)
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@ -1899,6 +1918,38 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
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}
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params.rope_freq_scale = std::stof(argv[i]);
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}
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else if (arg == "--yarn-ext-factor")
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{
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.yarn_ext_factor = std::stof(argv[i]);
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}
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else if (arg == "--yarn-attn-factor")
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{
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.yarn_attn_factor = std::stof(argv[i]);
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}
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else if (arg == "--yarn-beta-fast")
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{
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.yarn_beta_fast = std::stof(argv[i]);
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}
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else if (arg == "--yarn-beta-slow")
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{
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if (++i >= argc) {
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invalid_param = true;
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break;
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}
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params.yarn_beta_slow = std::stof(argv[i]);
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}
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else if (arg == "--memory-f32" || arg == "--memory_f32")
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{
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params.memory_f16 = false;
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@ -2213,8 +2264,8 @@ int main(int argc, char **argv)
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llama_backend_init(params.numa);
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LOG_INFO("build info", {{"build", BUILD_NUMBER},
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{"commit", BUILD_COMMIT}});
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LOG_INFO("build info", {{"build", LLAMA_BUILD_NUMBER},
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{"commit", LLAMA_COMMIT}});
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LOG_INFO("system info", {
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{"n_threads", params.n_threads},
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@ -3,6 +3,3 @@ add_executable(${TARGET} speculative.cpp)
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install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -349,9 +349,9 @@ static struct ggml_tensor * llama_build_train_graphs(
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// not capturing these, to silcence warnings
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const int rope_mode = 0;
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return ggml_rope_custom(ctx,
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t, KQ_pos, n_rot, rope_mode, n_ctx,
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rope_freq_base, rope_freq_scale);
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return ggml_rope_custom(
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ctx, t, KQ_pos, n_rot, rope_mode, n_ctx, 0, rope_freq_base, rope_freq_scale, 0.0f, 1.0f, 0.0f, 0.0f
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);
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};
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set_name(tokens_input, "tokens_input");
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