ikawrakow/ik_llama.cpp
1
0
Fork 0
mirror of https://github.com/ikawrakow/ik_llama.cpp.git synced 2026-02-06 22:40:09 +00:00
Code Issues Packages Projects Releases Wiki Activity

Q3_K_R4 (#134)

Browse Source 
* q3_k_r4: Zen4 works, but not as good as it should be

238 t/s, so sloghtly slower than q6_k_r4.

* q3_k_r4: NEON

We get PP-512(LLaMA-3.1-8B) = 106.9 t/s.
This is 1.93X faster than q3_K_S!

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
Kawrakow
2024-12-11 11:19:00 +01:00
committed by GitHub
parent e78e47b857
commit 4872f2f57e
10 changed files with 356 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

18
src/llama.cpp
View File

@@ -3836,6 +3836,7 @@ struct llama_model_loader {
case GGML_TYPE_Q8_0: ftype = LLAMA_FTYPE_MOSTLY_Q8_0; break;
case GGML_TYPE_Q2_K: ftype = LLAMA_FTYPE_MOSTLY_Q2_K; break;
case GGML_TYPE_Q3_K: ftype = LLAMA_FTYPE_MOSTLY_Q3_K_M; break;
case GGML_TYPE_Q3_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q3_K_R4; break;
case GGML_TYPE_Q4_K: ftype = LLAMA_FTYPE_MOSTLY_Q4_K_M; break;
case GGML_TYPE_Q4_K_R4: ftype = LLAMA_FTYPE_MOSTLY_Q4_K_R4; break;
case GGML_TYPE_Q5_K: ftype = LLAMA_FTYPE_MOSTLY_Q5_K_M; break;
@@ -4548,6 +4549,7 @@ static std::string llama_model_ftype_name(llama_ftype ftype) {
case LLAMA_FTYPE_MOSTLY_Q3_K_S: return "Q3_K - Small";
case LLAMA_FTYPE_MOSTLY_Q3_K_M: return "Q3_K - Medium";
case LLAMA_FTYPE_MOSTLY_Q3_K_L: return "Q3_K - Large";
case LLAMA_FTYPE_MOSTLY_Q3_K_R4: return "Q3_K_R4";
case LLAMA_FTYPE_MOSTLY_Q4_K_S: return "Q4_K - Small";
case LLAMA_FTYPE_MOSTLY_Q4_K_R4: return "Q4_K_R4";
case LLAMA_FTYPE_MOSTLY_Q4_K_M: return "Q4_K - Medium";
@@ -15792,6 +15794,9 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (new_type == GGML_TYPE_IQ4_XS_R4) {
new_type = GGML_TYPE_IQ4_XS;
}
else if (new_type == GGML_TYPE_Q3_K_R4) {
new_type = GGML_TYPE_Q3_K;
}
else if (new_type == GGML_TYPE_Q4_K_R4) {
new_type = GGML_TYPE_Q4_K;
}
@@ -15904,6 +15909,7 @@ 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_Q3_K_R4) new_type = GGML_TYPE_Q4_K_R4;
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_IQ4_NL_R4) new_type = GGML_TYPE_Q5_K;
@@ -15935,7 +15941,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
else if (ftype == LLAMA_FTYPE_MOSTLY_Q5_K_S) {
if (qs.model.hparams.n_vocab >= 127999 && (qs.model.type == MODEL_8B || qs.model.type == MODEL_70B))
new_type = GGML_TYPE_Q4_K;
}
}
} else if (name.find("ffn_down") != std::string::npos) {
auto info = layer_info(qs.i_ffn_down, qs.n_ffn_down, name.c_str());
int i_layer = info.first, n_layer = info.second;
@@ -16003,7 +16009,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S || ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_IQ3_S ||
ftype == LLAMA_FTYPE_MOSTLY_IQ3_M || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS || ftype == LLAMA_FTYPE_MOSTLY_IQ4_K ||
ftype == LLAMA_FTYPE_MOSTLY_IQ2_K || ftype == LLAMA_FTYPE_MOSTLY_IQ3_K || ftype == LLAMA_FTYPE_MOSTLY_Q4_K_R4 ||
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4) {
ftype == LLAMA_FTYPE_MOSTLY_IQ4_NL_R4 || ftype == LLAMA_FTYPE_MOSTLY_IQ4_XS_R4 || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_R4) {
new_type = GGML_TYPE_Q5_K;
}
} else {
@@ -16073,7 +16079,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
new_type == GGML_TYPE_IQ5_K || new_type == GGML_TYPE_IQ3_K || new_type == GGML_TYPE_Q4_K_R4 ||
new_type == GGML_TYPE_IQ6_K || new_type == GGML_TYPE_IQ4_KS || new_type == GGML_TYPE_IQ4_XS_R4 ||
new_type == GGML_TYPE_IQ2_KS || new_type == GGML_TYPE_IQ4_KSS || new_type == GGML_TYPE_Q6_K_R4 ||
new_type == GGML_TYPE_Q5_K_R4) {
new_type == GGML_TYPE_Q5_K_R4 || new_type == GGML_TYPE_Q3_K_R4) {
int nx = tensor->ne[0];
int ny = tensor->ne[1];
if (nx % QK_K != 0) {
@@ -16101,6 +16107,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
case GGML_TYPE_IQ1_M:
case GGML_TYPE_Q2_K:
case GGML_TYPE_Q3_K:
case GGML_TYPE_Q3_K_R4:
case GGML_TYPE_IQ2_K:
case GGML_TYPE_IQ3_K:
case GGML_TYPE_IQ4_KSS:
@@ -16201,6 +16208,7 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
case LLAMA_FTYPE_MOSTLY_Q3_K_S:
case LLAMA_FTYPE_MOSTLY_Q3_K_M:
case LLAMA_FTYPE_MOSTLY_Q3_K_L: default_type = GGML_TYPE_Q3_K; break;
case LLAMA_FTYPE_MOSTLY_Q3_K_R4: default_type = GGML_TYPE_Q3_K_R4; break;
case LLAMA_FTYPE_MOSTLY_Q4_K_S:
case LLAMA_FTYPE_MOSTLY_Q4_K_M: default_type = GGML_TYPE_Q4_K; break;
case LLAMA_FTYPE_MOSTLY_Q4_K_R4: default_type = GGML_TYPE_Q4_K_R4; break;
@@ -16608,6 +16616,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q8_0;
else chunk_size_multiplier = 4;
}
else if (new_type == GGML_TYPE_Q3_K_R4) {
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q3_K;
else chunk_size_multiplier = 4;
}
else if (new_type == GGML_TYPE_Q4_K_R4) {
if (tensor->ne[1] % 4 != 0) new_type = GGML_TYPE_Q4_K;
else chunk_size_multiplier = 4;