mirrors/ollama-for-amd
1
0
Fork 0
mirror of https://github.com/likelovewant/ollama-for-amd.git synced 2025-12-24 23:48:01 +00:00
Code Issues Packages Projects Releases Wiki Activity

Update GGML to b6646 (#12245)

Browse Source 
Notable EOLs with this change:
- MacOS v12 and v13 are no longer supported (v14+ required)
- AMD gfx900 and gfx906 are no longer supported
This commit is contained in:
Daniel Hiltgen
2025-10-02 14:47:10 -07:00
committed by GitHub
parent fdb109469f
commit c68f367ef6
326 changed files with 30615 additions and 20624 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
llama/llama.cpp/src/llama-quant.cpp vendored
View File

@@ -725,7 +725,9 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
// attention layers have a non-zero number of kv heads
int32_t n_attn_layer = model.hparams.n_layer - std::count(n_head_kv_iter, n_head_kv_iter + model.hparams.n_layer, 0);
if (llama_model_has_encoder(&model)) {
n_attn_layer *= 3;
// now n_attn_layer is the number of attention layers in the encoder
// for each decoder block, there are 2 attention layers
n_attn_layer += 2 * model.hparams.dec_n_layer;
}
GGML_ASSERT((qs.n_attention_wv == n_attn_layer - pruned_attention_w) && "n_attention_wv is unexpected");
}
@@ -920,7 +922,7 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
new_type = tensor->type;
new_data = tensor->data;
new_size = ggml_nbytes(tensor);
LLAMA_LOG_INFO("size = %8.3f MB\n", ggml_nbytes(tensor)/1024.0/1024.0);
LLAMA_LOG_INFO("size = %8.3f MiB\n", ggml_nbytes(tensor)/1024.0/1024.0);
} else {
const int64_t nelements = ggml_nelements(tensor);
@@ -1037,8 +1039,8 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
}
close_ofstream();
LLAMA_LOG_INFO("%s: model size = %8.2f MB\n", __func__, total_size_org/1024.0/1024.0);
LLAMA_LOG_INFO("%s: quant size = %8.2f MB\n", __func__, total_size_new/1024.0/1024.0);
LLAMA_LOG_INFO("%s: model size = %8.2f MiB\n", __func__, total_size_org/1024.0/1024.0);
LLAMA_LOG_INFO("%s: quant size = %8.2f MiB\n", __func__, total_size_new/1024.0/1024.0);
if (qs.n_fallback > 0) {
LLAMA_LOG_WARN("%s: WARNING: %d of %d tensor(s) required fallback quantization\n",