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-rw-r--r--common/common.h44
1 files changed, 22 insertions, 22 deletions
diff --git a/common/common.h b/common/common.h
index 72a49b89..9ad62563 100644
--- a/common/common.h
+++ b/common/common.h
@@ -43,29 +43,29 @@ extern char const *LLAMA_BUILD_TARGET;
int32_t get_num_physical_cores();
struct gpt_params {
- uint32_t seed = -1; // RNG seed
+ uint32_t seed = -1; // RNG seed
int32_t n_threads = get_num_physical_cores();
- int32_t n_threads_batch = -1; // number of threads to use for batch processing (-1 = use n_threads)
- int32_t n_predict = -1; // new tokens to predict
- int32_t n_ctx = 512; // context size
- int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
- int32_t n_keep = 0; // number of tokens to keep from initial prompt
- int32_t n_draft = 16; // number of tokens to draft during speculative decoding
- int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
- int32_t n_parallel = 1; // number of parallel sequences to decode
- int32_t n_sequences = 1; // number of sequences to decode
- int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
- int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
- int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
- float tensor_split[LLAMA_MAX_DEVICES] = {0}; // how split tensors should be distributed across GPUs
- int32_t n_beams = 0; // if non-zero then use beam search of given width.
- float rope_freq_base = 0.0f; // RoPE base frequency
- float rope_freq_scale = 0.0f; // RoPE frequency scaling factor
- float yarn_ext_factor = NAN; // YaRN extrapolation mix factor
- float yarn_attn_factor = 1.0f; // YaRN magnitude scaling factor
- float yarn_beta_fast = 32.0f;// YaRN low correction dim
- float yarn_beta_slow = 1.0f; // YaRN high correction dim
- int32_t yarn_orig_ctx = 0; // YaRN original context length
+ int32_t n_threads_batch = -1; // number of threads to use for batch processing (-1 = use n_threads)
+ int32_t n_predict = -1; // new tokens to predict
+ int32_t n_ctx = 512; // context size
+ int32_t n_batch = 512; // batch size for prompt processing (must be >=32 to use BLAS)
+ int32_t n_keep = 0; // number of tokens to keep from initial prompt
+ int32_t n_draft = 16; // number of tokens to draft during speculative decoding
+ int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
+ int32_t n_parallel = 1; // number of parallel sequences to decode
+ int32_t n_sequences = 1; // number of sequences to decode
+ int32_t n_gpu_layers = -1; // number of layers to store in VRAM (-1 - use default)
+ int32_t n_gpu_layers_draft = -1; // number of layers to store in VRAM for the draft model (-1 - use default)
+ int32_t main_gpu = 0; // the GPU that is used for scratch and small tensors
+ float tensor_split[LLAMA_MAX_DEVICES] = {0}; // how split tensors should be distributed across GPUs
+ int32_t n_beams = 0; // if non-zero then use beam search of given width.
+ float rope_freq_base = 0.0f; // RoPE base frequency
+ float rope_freq_scale = 0.0f; // RoPE frequency scaling factor
+ float yarn_ext_factor = -1.0f; // YaRN extrapolation mix factor
+ float yarn_attn_factor = 1.0f; // YaRN magnitude scaling factor
+ float yarn_beta_fast = 32.0f; // YaRN low correction dim
+ float yarn_beta_slow = 1.0f; // YaRN high correction dim
+ int32_t yarn_orig_ctx = 0; // YaRN original context length
int8_t rope_scaling_type = LLAMA_ROPE_SCALING_UNSPECIFIED;
// // sampling parameters