ikawrakow/ik_llama.cpp
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iq2_k: slightly better bpw - accuracy compromise (#20)

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For LLaMA-3.1 models:
* It is better to quantize all of attn_v with iq3_k instead of
  half of attn_v with iq4_k
* Quantizing attn_output with iq3_k results in a larger PPL decrease
  compared to what one expects from the added bpw.

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
Kawrakow
2024-08-19 13:36:51 +03:00
committed by GitHub
parent a58853bf5e
commit 041d79925c
1 changed files with 19 additions and 2 deletions
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21
src/llama.cpp
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@@ -15578,6 +15578,18 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
auto use_more_bits = [](int i_layer, int n_layers) -> bool {
return i_layer < n_layers/8 || i_layer >= 7*n_layers/8 || (i_layer - n_layers/8)%3 == 2;
};
//auto get_layer = [] (const char * name) {
// int il;
// if (sscanf(name, "blk.%d.", &il) == 1) return il;
// return -1;
//};
//int il = get_layer(tensor->name);
//int nl = qs.model.hparams.n_layer;
//if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_K && (il == 0 || il == nl-1)) {
// return GGML_TYPE_IQ3_K;
//}
const int n_expert = std::max(1, (int)qs.model.hparams.n_expert);
auto layer_info = [n_expert] (int i_layer, int n_layer, const char * name) {
if (n_expert > 1) {
@@ -15625,6 +15637,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_S || ftype == LLAMA_FTYPE_MOSTLY_IQ2_M) {
new_type = GGML_TYPE_IQ3_S;
}
//else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_K) {
// new_type = GGML_TYPE_IQ3_K;
//}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_XXS) {
new_type = GGML_TYPE_IQ3_S;
}
@@ -15668,7 +15683,8 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
new_type = qs.model.hparams.n_gqa() >= 4 ? GGML_TYPE_Q4_K : GGML_TYPE_Q3_K;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_K) {
if (use_more_bits(qs.i_attention_wv, qs.n_attention_wv)) new_type = GGML_TYPE_IQ4_K;
//if (use_more_bits(qs.i_attention_wv, qs.n_attention_wv)) new_type = GGML_TYPE_IQ4_K;
new_type = GGML_TYPE_IQ3_K;
}
else if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K_S && qs.model.hparams.n_gqa() >= 4) {
new_type = GGML_TYPE_Q4_K;
@@ -15706,7 +15722,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (qs.model.hparams.n_gqa() >= 4) {
if (new_type == GGML_TYPE_Q2_K || new_type == GGML_TYPE_IQ3_XXS) new_type = GGML_TYPE_IQ3_S;
else if (new_type == GGML_TYPE_Q3_K || new_type == GGML_TYPE_IQ3_S ) new_type = GGML_TYPE_Q4_K;
else if (new_type == GGML_TYPE_Q4_K || new_type == GGML_TYPE_IQ4_XS || new_type == GGML_TYPE_IQ4_K) new_type = GGML_TYPE_Q5_K;
else if (new_type == GGML_TYPE_Q4_K || new_type == GGML_TYPE_IQ4_XS) new_type = GGML_TYPE_Q5_K;
else if (new_type == GGML_TYPE_IQ4_NL) new_type = GGML_TYPE_Q5_K;
else if (new_type == GGML_TYPE_Q5_K) new_type = GGML_TYPE_Q6_K;
}
@@ -15791,6 +15807,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M ) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L ) new_type = GGML_TYPE_Q5_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ3_M ) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_IQ2_K ) new_type = GGML_TYPE_IQ3_K;
}
} else {
if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q4_K;