@@ -15900,11 +15900,12 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
1590015900 new_type = GGML_TYPE_IQ2_S;
1590115901 }
1590215902 else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) new_type = GGML_TYPE_IQ3_XXS;
15903+ else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_XL) new_type = GGML_TYPE_IQ3_XXS;
1590315904 else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) new_type = GGML_TYPE_IQ3_S;
1590415905 else if (new_type == GGML_TYPE_Q4_0_4_4 || new_type == GGML_TYPE_Q4_0_4_8 || new_type == GGML_TYPE_Q4_0_8_8) {
1590515906 new_type = GGML_TYPE_Q4_0;
1590615907 }
15907- else if (ftype == LLAMA_FTYPE_MOSTLY_IQ4_XSR ) new_type = GGML_TYPE_IQ4_XS;
15908+ else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL ) new_type = GGML_TYPE_IQ4_XS;
1590815909 }
1590915910 } else if (name.find("attn_v.weight") != std::string::npos) {
1591015911 if (ftype == LLAMA_FTYPE_CQS && qs.params->attn_v_type < GGML_TYPE_COUNT) {
@@ -16010,9 +16011,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
1601016011 else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XS && qs.model.hparams.n_gqa() < 2 && qs.model.hparams.n_expert < 2) {
1601116012 new_type = GGML_TYPE_IQ3_XXS;
1601216013 }
16013- else if (( ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) &&
16014- (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2)) {
16015- new_type = GGML_TYPE_IQ4_XS;
16014+ else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ3_XL) {
16015+ if (qs.model.hparams.n_gqa() >= 4 || qs.model.hparams.n_expert >= 2) new_type = GGML_TYPE_Q5_K;
16016+ else if (qs.model.hparams.n_gqa() >= 2) new_type = GGML_TYPE_IQ4_XS;
1601616017 }
1601716018 else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L && (qs.model.hparams.n_gqa() >= 2 || qs.model.hparams.n_expert >= 2)) {
1601816019 new_type = GGML_TYPE_Q4_K;
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