@@ -19447,6 +19447,18 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
1944719447 }
1944819448 } else if (name.find("attn_v.weight") != std::string::npos) {
1944919449 if (qs.params->attn_v_type < GGML_TYPE_COUNT) new_type = qs.params->attn_v_type;
19450+ else if (qs.model.hparams.n_expert >= 4) {
19451+ // for the 4-8-expert model, bumping this to Q8_0 trades just ~128MB
19452+ // TODO: explore better strategies
19453+ new_type = GGML_TYPE_Q8_0;
19454+ }
19455+ else if (qs.model.type == MODEL_70B) {
19456+ // In the 70B model we have 8 heads sharing the same attn_v weights. As a result, the attn_v.weight tensor is
19457+ // 8x smaller compared to attn_q.weight. Hence, we can get a nice boost in quantization accuracy with
19458+ // nearly negligible increase in model size by quantizing this tensor with more bits:
19459+ if (new_type == GGML_TYPE_Q3_K || new_type == GGML_TYPE_Q4_K) new_type = GGML_TYPE_Q5_K;
19460+ if (new_type == GGML_TYPE_IQ3_K) new_type = GGML_TYPE_IQ5_K;
19461+ }
1945019462 else if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K) {
1945119463 new_type = qs.model.hparams.n_gqa() >= 4 ? GGML_TYPE_Q4_K : GGML_TYPE_Q3_K;
1945219464 }
@@ -19531,18 +19543,6 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
1953119543 if (qs.model.hparams.n_vocab >= 127999 && (qs.model.type == MODEL_8B || qs.model.type == MODEL_70B))
1953219544 new_type = GGML_TYPE_IQ6_K;
1953319545 }
19534- if (qs.model.type == MODEL_70B) {
19535- // In the 70B model we have 8 heads sharing the same attn_v weights. As a result, the attn_v.weight tensor is
19536- // 8x smaller compared to attn_q.weight. Hence, we can get a nice boost in quantization accuracy with
19537- // nearly negligible increase in model size by quantizing this tensor with more bits:
19538- if (new_type == GGML_TYPE_Q3_K || new_type == GGML_TYPE_Q4_K) new_type = GGML_TYPE_Q5_K;
19539- if (new_type == GGML_TYPE_IQ3_K) new_type = GGML_TYPE_IQ5_K;
19540- }
19541- if (qs.model.hparams.n_expert >= 4) {
19542- // for the 4-8-expert model, bumping this to Q8_0 trades just ~128MB
19543- // TODO: explore better strategies
19544- new_type = GGML_TYPE_Q8_0;
19545- }
1954619546 else if (qs.model.hparams.n_gqa() >= 4) {
1954719547 if (new_type == GGML_TYPE_Q2_K || new_type == GGML_TYPE_IQ3_XXS) new_type = GGML_TYPE_IQ3_S;
1954819548 else if (new_type == GGML_TYPE_Q2_K_R4 || new_type == GGML_TYPE_IQ3_XXS_R4) new_type = GGML_TYPE_IQ3_K_R4;
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