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Merge branch 'upstream' into concedo_experimental
# Conflicts: # .devops/llama-server-cuda.Dockerfile # .devops/llama-server-rocm.Dockerfile # .devops/llama-server-vulkan.Dockerfile # .devops/llama-server.Dockerfile # .github/workflows/docker.yml # README.md # llama.cpp # tests/test-chat-template.cpp # tests/test-grammar-integration.cpp # tests/test-json-schema-to-grammar.cpp # tests/test-llama-grammar.cpp
This commit is contained in:
commit
f3dfa96dbc
29 changed files with 2097 additions and 431 deletions
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@ -48,6 +48,12 @@ int32_t cpu_get_num_math();
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// CLI argument parsing
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//
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// dimensionality reduction methods, used by cvector-generator
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enum dimre_method {
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DIMRE_METHOD_PCA,
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DIMRE_METHOD_MEAN,
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};
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struct gpt_params {
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uint32_t seed = LLAMA_DEFAULT_SEED; // RNG seed
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@ -255,13 +261,12 @@ struct gpt_params {
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bool compute_ppl = true; // whether to compute perplexity
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// cvector-generator params
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int n_completions = 64;
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int n_pca_batch = 20;
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int n_pca_batch = 100;
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int n_pca_iterations = 1000;
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std::string cvector_outfile = "control_vector.gguf";
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std::string cvector_completions_file = "examples/cvector-generator/completions.txt";
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std::string cvector_positive_file = "examples/cvector-generator/positive.txt";
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std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
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dimre_method cvector_dimre_method = DIMRE_METHOD_PCA;
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std::string cvector_outfile = "control_vector.gguf";
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std::string cvector_positive_file = "examples/cvector-generator/positive.txt";
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std::string cvector_negative_file = "examples/cvector-generator/negative.txt";
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};
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void gpt_params_handle_model_default(gpt_params & params);
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@ -382,9 +387,32 @@ bool llama_should_add_bos_token(const llama_model * model);
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// Chat template utils
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//
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// same with llama_chat_message, but uses std::string
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struct llama_chat_msg {
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std::string role;
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std::string content;
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};
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// Check if the template supplied via "--chat-template" is supported or not. Returns true if it's valid
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bool llama_chat_verify_template(const std::string & tmpl);
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// CPP wrapper for llama_chat_apply_template
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std::string llama_chat_apply_template(const struct llama_model * model,
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const std::string & tmpl,
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const std::vector<llama_chat_msg> & chat,
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bool add_ass);
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// Format single message, while taking into account the position of that message in chat history
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std::string llama_chat_format_single(const struct llama_model * model,
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const std::string & tmpl,
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const std::vector<llama_chat_msg> & past_msg,
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const llama_chat_msg & new_msg,
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bool add_ass);
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// Returns an example of formatted chat
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std::string llama_chat_format_example(const struct llama_model * model,
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const std::string & tmpl);
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//
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// KV cache utils
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//
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