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https://github.com/ggerganov/llama.cpp.git
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commit
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@ -43,29 +43,29 @@ extern char const *LLAMA_BUILD_TARGET;
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int32_t get_num_physical_cores();
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int32_t get_num_physical_cores();
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struct gpt_params {
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struct gpt_params {
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uint32_t seed = -1; // RNG seed
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uint32_t seed = -1; // RNG seed
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int32_t n_threads = get_num_physical_cores();
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int32_t n_threads = get_num_physical_cores();
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int32_t n_threads_batch = -1; // number of threads to use for batch processing (-1 = use n_threads)
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int32_t n_threads_batch = -1; // number of threads to use for batch processing (-1 = use n_threads)
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int32_t n_predict = -1; // new tokens to predict
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int32_t n_predict = -1; // new tokens to predict
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int32_t n_ctx = 512; // context size
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int32_t n_ctx = 512; // context size
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int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
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int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
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int32_t n_keep = 0; // number of tokens to keep from initial prompt
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int32_t n_keep = 0; // number of tokens to keep from initial prompt
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int32_t n_draft = 16; // number of tokens to draft during speculative decoding
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int32_t n_draft = 16; // number of tokens to draft during speculative decoding
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int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
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int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
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int32_t n_parallel = 1; // number of parallel sequences to decode
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int32_t n_parallel = 1; // number of parallel sequences to decode
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int32_t n_sequences = 1; // number of sequences to decode
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int32_t n_sequences = 1; // number of sequences to decode
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int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
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int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
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int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
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int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
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int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
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int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
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float tensor_split[LLAMA_MAX_DEVICES] = {0}; // how split tensors should be distributed across GPUs
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float tensor_split[LLAMA_MAX_DEVICES] = {0}; // how split tensors should be distributed across GPUs
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int32_t n_beams = 0; // if non-zero then use beam search of given width.
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int32_t n_beams = 0; // if non-zero then use beam search of given width.
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float rope_freq_base = 0.0f; // RoPE base frequency
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float rope_freq_base = 0.0f; // RoPE base frequency
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float rope_freq_scale = 0.0f; // RoPE frequency scaling factor
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float rope_freq_scale = 0.0f; // RoPE frequency scaling factor
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float yarn_ext_factor = NAN; // YaRN extrapolation mix factor
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float yarn_ext_factor = -1.0f; // YaRN extrapolation mix factor
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float yarn_attn_factor = 1.0f; // YaRN magnitude scaling factor
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float yarn_attn_factor = 1.0f; // YaRN magnitude scaling factor
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float yarn_beta_fast = 32.0f;// YaRN low correction dim
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float yarn_beta_fast = 32.0f; // YaRN low correction dim
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float yarn_beta_slow = 1.0f; // YaRN high correction dim
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float yarn_beta_slow = 1.0f; // YaRN high correction dim
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int32_t yarn_orig_ctx = 0; // YaRN original context length
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int32_t yarn_orig_ctx = 0; // YaRN original context length
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int8_t rope_scaling_type = LLAMA_ROPE_SCALING_UNSPECIFIED;
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int8_t rope_scaling_type = LLAMA_ROPE_SCALING_UNSPECIFIED;
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// // sampling parameters
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// // sampling parameters
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10
llama.h
10
llama.h
@ -175,11 +175,11 @@ extern "C" {
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};
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};
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struct llama_context_params {
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struct llama_context_params {
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uint32_t seed; // RNG seed, -1 for random
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uint32_t seed; // RNG seed, -1 for random
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uint32_t n_ctx; // text context, 0 = from model
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uint32_t n_ctx; // text context, 0 = from model
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uint32_t n_batch; // prompt processing maximum batch size
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uint32_t n_batch; // prompt processing maximum batch size
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uint32_t n_threads; // number of threads to use for generation
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uint32_t n_threads; // number of threads to use for generation
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uint32_t n_threads_batch; // number of threads to use for batch processing
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uint32_t n_threads_batch; // number of threads to use for batch processing
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int8_t rope_scaling_type; // RoPE scaling type, from `enum llama_rope_scaling_type`
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int8_t rope_scaling_type; // RoPE scaling type, from `enum llama_rope_scaling_type`
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// ref: https://github.com/ggerganov/llama.cpp/pull/2054
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// ref: https://github.com/ggerganov/llama.cpp/pull/2054
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