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https://github.com/ggerganov/llama.cpp.git
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f66f582927
* llama : scatter llama.cpp into multiple modules (wip) * llama : control-vector -> adapter * llama : arch * llama : mmap ggml-ci * ci : remove BUILD_SHARED_LIBS=OFF ggml-ci * llama : arch (cont) ggml-ci * llama : chat ggml-ci * llama : model ggml-ci * llama : hparams ggml-ci * llama : adapter ggml-ci * examples : fix ggml-ci * rebase ggml-ci * minor * llama : kv cache ggml-ci * llama : impl ggml-ci * llama : batch ggml-ci * cont ggml-ci * llama : context ggml-ci * minor * llama : context (cont) ggml-ci * llama : model loader ggml-ci * common : update lora ggml-ci * llama : quant ggml-ci * llama : quant (cont) ggml-ci * minor [no ci]
38 lines
934 B
C++
38 lines
934 B
C++
#pragma once
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#include "llama.h"
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#include <cstdint>
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struct llama_cparams {
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uint32_t n_ctx; // context size used during inference
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uint32_t n_batch;
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uint32_t n_ubatch;
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uint32_t n_seq_max;
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int n_threads; // number of threads to use for generation
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int n_threads_batch; // number of threads to use for batch processing
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float rope_freq_base;
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float rope_freq_scale;
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uint32_t n_ctx_orig_yarn;
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// These hyperparameters are not exposed in GGUF, because all
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// existing YaRN models use the same values for them.
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float yarn_ext_factor;
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float yarn_attn_factor;
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float yarn_beta_fast;
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float yarn_beta_slow;
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float defrag_thold;
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bool embeddings;
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bool causal_attn;
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bool offload_kqv;
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bool flash_attn;
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bool no_perf;
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enum llama_pooling_type pooling_type;
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ggml_backend_sched_eval_callback cb_eval;
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void * cb_eval_user_data;
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};
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