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https://github.com/ggml-org/llama.cpp.git
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Merge branch 'master' into xsn/private_batch_api
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@@ -178,10 +178,10 @@ struct common_params_speculative {
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int32_t n_ctx = 0; // draft context size
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int32_t n_max = 16; // maximum number of tokens to draft during speculative decoding
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int32_t n_min = 5; // minimum number of draft tokens to use for speculative decoding
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int32_t n_min = 0; // minimum number of draft tokens to use for speculative decoding
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int32_t n_gpu_layers = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
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float p_split = 0.1f; // speculative decoding split probability
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float p_min = 0.9f; // minimum speculative decoding probability (greedy)
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float p_min = 0.75f; // minimum speculative decoding probability (greedy)
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struct cpu_params cpuparams;
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struct cpu_params cpuparams_batch;
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@@ -618,62 +618,6 @@ std::string common_detokenize(
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const std::vector<llama_token> & tokens,
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bool special = true);
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//
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// Chat template utils
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//
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struct common_tool_call {
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std::string name;
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std::string arguments;
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std::string id;
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};
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// same with llama_chat_message, but uses std::string
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struct common_chat_msg {
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std::string role;
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std::string content;
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std::vector<common_tool_call> tool_calls;
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std::string reasoning_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 common_chat_verify_template(const std::string & tmpl, bool use_jinja);
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namespace minja {
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class chat_template;
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}
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typedef minja::chat_template common_chat_template;
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struct common_chat_templates {
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bool has_explicit_template; // Model had builtin template or template overridde was specified.
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std::unique_ptr<common_chat_template> template_default; // always set (defaults to chatml)
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std::unique_ptr<common_chat_template> template_tool_use;
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};
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// CPP wrapper for llama_chat_apply_template
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// If the built-in template is not supported, we default to chatml
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// If the custom "tmpl" is not supported, we throw an error
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std::string common_chat_apply_template(
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const common_chat_template & tmpl,
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const std::vector<common_chat_msg> & chat,
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bool add_ass,
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bool use_jinja);
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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 common_chat_format_single(
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const common_chat_template & tmpl,
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const std::vector<common_chat_msg> & past_msg,
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const common_chat_msg & new_msg,
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bool add_ass,
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bool use_jinja);
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// Returns an example of formatted chat
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std::string common_chat_format_example(
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const common_chat_template & tmpl, bool use_jinja);
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common_chat_templates common_chat_templates_from_model(const struct llama_model * model, const std::string & chat_template_override);
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//
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// KV cache utils
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//
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