aditya/llama.cpp
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llama : only use Q6_K for output weights if tensor size is multiple of 256 (#1932)

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* Only use Q6_K for output weights if tensor size is multiple of 256

* Fixed copy/paste mistake

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
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Kawrakow 2023-06-19 18:17:03 +03:00 committed by GitHub
parent ca7c3f4da5
commit cb40dfca69
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1 changed files with 6 additions and 2 deletions
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llama.cpp
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@ -2495,7 +2495,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
if (quantized_type == GGML_TYPE_Q2_K || quantized_type == GGML_TYPE_Q3_K || quantized_type == GGML_TYPE_Q4_K ||
quantized_type == GGML_TYPE_Q5_K || quantized_type == GGML_TYPE_Q6_K) {
int nx = tensor.ne.at(0);
int ny = tensor.ne.at(0);
int ny = tensor.ne.at(1);
if (nx % QK_K != 0 || ny % QK_K != 0) {
fprintf(stderr, "\n\n========================= Tensor sizes %d x %d are not divisible by %d\n",nx,ny,QK_K);
fprintf(stderr, "This is required to be able to use k-quants for now!\n");
@ -2504,7 +2504,11 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
}
}
if (tensor.name == "output.weight") {
new_type = GGML_TYPE_Q6_K;
int nx = tensor.ne.at(0);
int ny = tensor.ne.at(1);
if (nx % QK_K == 0 && ny % QK_K == 0) {
new_type = GGML_TYPE_Q6_K;
}
} else if (tensor.name.find("attention.wv.weight") != std::string::npos) {
if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K;