ikawrakow/ik_llama.cpp
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Fix very low bpw missing imatrix check (#1284)

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Kawrakow
2026-02-19 08:15:26 +01:00
committed by GitHub
parent 51df09be8a
commit d81cde5cea
1 changed files with 21 additions and 17 deletions
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38
src/llama-quantize.cpp
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@@ -1425,23 +1425,27 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
} }
} }
} }
if (!params->ignore_imatrix_rules && !imatrix && if (!params->ignore_imatrix_rules && !imatrix) {
(new_type == GGML_TYPE_IQ2_XXS || bool is_very_low_bpw_quant = new_type == GGML_TYPE_IQ2_XXS ||
new_type == GGML_TYPE_IQ2_XXS_R4 || new_type == GGML_TYPE_IQ2_XXS_R4 ||
new_type == GGML_TYPE_IQ2_XS || new_type == GGML_TYPE_IQ2_XS ||
new_type == GGML_TYPE_IQ2_XS_R4 || new_type == GGML_TYPE_IQ2_XS_R4 ||
new_type == GGML_TYPE_IQ2_S || new_type == GGML_TYPE_IQ2_S ||
new_type == GGML_TYPE_IQ2_S_R4|| new_type == GGML_TYPE_IQ2_S_R4 ||
new_type == GGML_TYPE_IQ1_S || new_type == GGML_TYPE_IQ1_S ||
new_type == GGML_TYPE_IQ1_S_R4|| new_type == GGML_TYPE_IQ1_S_R4 ||
new_type == GGML_TYPE_IQ1_M_R4|| new_type == GGML_TYPE_IQ1_M ||
(new_type == GGML_TYPE_IQ1_M && strcmp(tensor->name, "token_embd.weight") && strcmp(tensor->name, "output.weight")) || new_type == GGML_TYPE_IQ1_M_R4 ||
(new_type == GGML_TYPE_Q2_K && ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S && strcmp(tensor->name, "token_embd.weight") != 0))) { new_type == GGML_TYPE_IQ1_KT ||
LLAMA_LOG_ERROR("\n\n============================================================\n"); new_type == GGML_TYPE_IQ2_KT ||
LLAMA_LOG_ERROR("Missing importance matrix for tensor %s in a very low-bit quantization\n", tensor->name); (new_type == GGML_TYPE_Q2_K && ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S);
LLAMA_LOG_ERROR("The result will be garbage, so bailing out\n"); if (is_very_low_bpw_quant && strcmp(tensor->name, "token_embd.weight") && strcmp(tensor->name, "output.weight")) {
LLAMA_LOG_ERROR("============================================================\n\n"); LLAMA_LOG_ERROR("\n\n============================================================\n");
throw std::runtime_error(format("Missing importance matrix for tensor %s in a very low-bit quantization", tensor->name)); LLAMA_LOG_ERROR("Missing importance matrix for tensor %s in a very low-bit quantization\n", tensor->name);
LLAMA_LOG_ERROR("The result will be garbage, so bailing out\n");
LLAMA_LOG_ERROR("============================================================\n\n");
throw std::runtime_error(format("Missing importance matrix for tensor %s in a very low-bit quantization", tensor->name));
}
} }
float * f32_data; float * f32_data;