Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Better perplexity for 2- and 3-bit quantization for LLaMA-v2-70B #2807

Merged
merged 2 commits into from
Aug 26, 2023
Merged

Better perplexity for 2- and 3-bit quantization for LLaMA-v2-70B #2807

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
6544756
Better perplexity for 2- and 3-bit quantization for the 70B model
Kawrakow Aug 26, 2023
3979af1
PR comment
Kawrakow Aug 26, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 14 additions & 0 deletions llama.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4653,6 +4653,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s

std::unique_ptr<llama_model_loader> ml(new llama_model_loader(fname_inp, /*use_mmap*/ false));

llama_model model;
llm_load_arch(*ml, model);
llm_load_hparams(*ml, model, 0, 0, 0);

const size_t align = GGUF_DEFAULT_ALIGNMENT;
struct gguf_context * ctx_out = gguf_init_empty();

Expand All @@ -4678,6 +4682,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
++n_feed_forward_w2;
}
}
if (n_attention_wv != n_feed_forward_w2 || (uint32_t)n_attention_wv != model.hparams.n_layer) {
LLAMA_LOG_WARN("%s ============ Strange model: n_attention_wv = %d, n_feed_forward_w2 = %d, hparams.n_layer = %d\n",
__func__, n_attention_wv, n_feed_forward_w2, model.hparams.n_layer);
}

int i_attention_wv = 0;
int i_feed_forward_w2 = 0;
Expand Down Expand Up @@ -4769,6 +4777,12 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S && i_attention_wv < 4) new_type = GGML_TYPE_Q5_K;
else if (QK_K == 64 && (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_S) &&
(i_attention_wv < n_attention_wv/8 || i_attention_wv >= 7*n_attention_wv/8)) new_type = GGML_TYPE_Q6_K;
if (model.type == MODEL_70B) {
// In the 70B model we have 8 heads sharing the same attn_v weights. As a result, the attn_v.weight tensor is
// 8x smaller compared to attn_q.weight. Hence, we can get a nice boost in quantization accuracy with
// nearly negligible increase in model size by quantizing this tensor with more bits:
if (new_type == GGML_TYPE_Q3_K || new_type == GGML_TYPE_Q4_K) new_type = GGML_TYPE_Q5_K;
}
++i_attention_wv;
} else if (name.find("ffn_down.weight") != std::string::npos) {
if (ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q3_K;
Expand Down