diff options
Diffstat (limited to 'examples/quantize')
| -rw-r--r-- | examples/quantize/quantize.cpp | 31 |
1 files changed, 26 insertions, 5 deletions
diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp index 0a91b537..60cf260c 100644 --- a/examples/quantize/quantize.cpp +++ b/examples/quantize/quantize.cpp @@ -142,11 +142,12 @@ static bool try_parse_ftype(const std::string & ftype_str_in, llama_ftype & ftyp // [[noreturn]] static void usage(const char * executable) { - printf("usage: %s [--help] [--allow-requantize] [--leave-output-tensor] [--pure] [--imatrix] [--include-weights] [--exclude-weights] [--output-tensor-type] [--token-embedding-type] [--attn-q-type] [--attn-k-type] [--attn-v-type] [--attn-qkv-type] [--attn-output-type] [--ffn-gate-type] [--ffn-down-type] [--ffn-up-type] [--keep-split] [--override-kv] model-f32.gguf [model-quant.gguf] type [nthreads]\n\n", executable); + printf("usage: %s [--help] [--allow-requantize] [--leave-output-tensor] [--pure] [--imatrix] [--hide-imatrix] [--include-weights] [--exclude-weights] [--output-tensor-type] [--token-embedding-type] [--attn-q-type] [--attn-k-type] [--attn-v-type] [--attn-qkv-type] [--attn-output-type] [--ffn-gate-type] [--ffn-down-type] [--ffn-up-type] [--keep-split] [--override-kv] model-f32.gguf [model-quant.gguf] type [nthreads]\n\n", executable); printf(" --allow-requantize: Allows requantizing tensors that have already been quantized. Warning: This can severely reduce quality compared to quantizing from 16bit or 32bit\n"); printf(" --leave-output-tensor: Will leave output.weight un(re)quantized. Increases model size but may also increase quality, especially when requantizing\n"); printf(" --pure: Disable k-quant mixtures and quantize all tensors to the same type\n"); printf(" --imatrix file_name: use data in file_name as importance matrix for quant optimizations\n"); + printf(" --hide-imatrix: do not store imatrix details in the quantized model\n"); printf(" --include-weights tensor_name: use importance matrix for this/these tensor(s)\n"); printf(" --exclude-weights tensor_name: use importance matrix for this/these tensor(s)\n"); printf(" --output-tensor-type ggml_type: use this ggml_type for the output.weight tensor.\n"); @@ -337,6 +338,8 @@ int main(int argc, char ** argv) { std::vector<std::string> repack_patterns; + bool hide_imatrix = false; + for (; arg_idx < argc && strncmp(argv[arg_idx], "--", 2) == 0; arg_idx++) { if (strcmp(argv[arg_idx], "--leave-output-tensor") == 0) { params.quantize_output_tensor = false; @@ -429,6 +432,8 @@ int main(int argc, char ** argv) { } else { usage(argv[0]); } + } else if (strcmp(argv[arg_idx], "--hide-imatrix") == 0) { + hide_imatrix = true; } else if (strcmp(argv[arg_idx], "--include-weights") == 0) { if (arg_idx < argc-1) { included_weights.emplace_back(argv[++arg_idx]); @@ -469,7 +474,11 @@ int main(int argc, char ** argv) { llama_model_kv_override kvo; std::strcpy(kvo.key, LLM_KV_QUANTIZE_IMATRIX_FILE); kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR; - strncpy(kvo.val_str, imatrix_file.c_str(), 127); + if (hide_imatrix) { + strncpy(kvo.val_str, "top_secret", 127); + } else { + strncpy(kvo.val_str, imatrix_file.c_str(), 127); + } kvo.val_str[127] = '\0'; kv_overrides.emplace_back(std::move(kvo)); } @@ -477,7 +486,11 @@ int main(int argc, char ** argv) { llama_model_kv_override kvo; std::strcpy(kvo.key, LLM_KV_QUANTIZE_IMATRIX_DATASET); kvo.tag = LLAMA_KV_OVERRIDE_TYPE_STR; - strncpy(kvo.val_str, imatrix_dataset.c_str(), 127); + if (hide_imatrix) { + strncpy(kvo.val_str, "top_secret", 127); + } else { + strncpy(kvo.val_str, imatrix_dataset.c_str(), 127); + } kvo.val_str[127] = '\0'; kv_overrides.emplace_back(std::move(kvo)); } @@ -486,7 +499,11 @@ int main(int argc, char ** argv) { llama_model_kv_override kvo; std::strcpy(kvo.key, LLM_KV_QUANTIZE_IMATRIX_N_ENTRIES); kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; - kvo.val_i64 = imatrix_data.size(); + if (hide_imatrix) { + kvo.val_i64 = 0; + } else { + kvo.val_i64 = imatrix_data.size(); + } kv_overrides.emplace_back(std::move(kvo)); } @@ -494,7 +511,11 @@ int main(int argc, char ** argv) { llama_model_kv_override kvo; std::strcpy(kvo.key, LLM_KV_QUANTIZE_IMATRIX_N_CHUNKS); kvo.tag = LLAMA_KV_OVERRIDE_TYPE_INT; - kvo.val_i64 = m_last_call; + if (hide_imatrix) { + kvo.val_i64 = 0; + } else { + kvo.val_i64 = m_last_call; + } kv_overrides.emplace_back(std::move(kvo)); } } |