diff options
| author | Kawrakow <iwankawrakow@gmail.com> | 2024-10-10 18:21:24 +0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2024-10-10 18:21:24 +0300 |
| commit | 70aca0b75c7b6658cdb5fe9d098d1fbda629e907 (patch) | |
| tree | 71b066ffce556d9249dc0584a39900ac5db452da /src/llama.cpp | |
| parent | b30c9e10d8710a49b2d2ab98d086b9f11bfaa228 (diff) | |
Better model info (#84)
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'src/llama.cpp')
| -rw-r--r-- | src/llama.cpp | 34 |
1 files changed, 28 insertions, 6 deletions
diff --git a/src/llama.cpp b/src/llama.cpp index 80104303..789e2a7c 100644 --- a/src/llama.cpp +++ b/src/llama.cpp @@ -5882,18 +5882,40 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) { LLAMA_LOG_INFO("%s: model type = %s\n", __func__, llama_model_type_name(model.type)); LLAMA_LOG_INFO("%s: model ftype = %s\n", __func__, llama_model_ftype_name(model.ftype).c_str()); if (ml.n_elements >= 1e12) { - LLAMA_LOG_INFO("%s: model params = %.2f T\n", __func__, ml.n_elements*1e-12); + LLAMA_LOG_INFO("%s: model params = %.3f T\n", __func__, ml.n_elements*1e-12); } else if (ml.n_elements >= 1e9) { - LLAMA_LOG_INFO("%s: model params = %.2f B\n", __func__, ml.n_elements*1e-9); + LLAMA_LOG_INFO("%s: model params = %.3f B\n", __func__, ml.n_elements*1e-9); } else if (ml.n_elements >= 1e6) { - LLAMA_LOG_INFO("%s: model params = %.2f M\n", __func__, ml.n_elements*1e-6); + LLAMA_LOG_INFO("%s: model params = %.3f M\n", __func__, ml.n_elements*1e-6); } else { - LLAMA_LOG_INFO("%s: model params = %.2f K\n", __func__, ml.n_elements*1e-3); + LLAMA_LOG_INFO("%s: model params = %.3f K\n", __func__, ml.n_elements*1e-3); } if (ml.n_bytes < GiB) { - LLAMA_LOG_INFO("%s: model size = %.2f MiB (%.2f BPW) \n", __func__, ml.n_bytes/1024.0/1024.0, ml.n_bytes*8.0/ml.n_elements); + LLAMA_LOG_INFO("%s: model size = %.3f MiB (%.3f BPW) \n", __func__, ml.n_bytes/1024.0/1024.0, ml.n_bytes*8.0/ml.n_elements); } else { - LLAMA_LOG_INFO("%s: model size = %.2f GiB (%.2f BPW) \n", __func__, ml.n_bytes/1024.0/1024.0/1024.0, ml.n_bytes*8.0/ml.n_elements); + LLAMA_LOG_INFO("%s: model size = %.3f GiB (%.3f BPW) \n", __func__, ml.n_bytes/1024.0/1024.0/1024.0, ml.n_bytes*8.0/ml.n_elements); + } + { + auto n_bytes = ml.n_bytes; + auto n_elements = ml.n_elements; + auto meta_tke = ml.get_tensor_meta("token_embd.weight"); + auto meta_out = ml.get_tensor_meta("output.weight"); + if (meta_tke && meta_out) { + n_bytes -= ggml_nbytes(meta_tke); + n_elements -= ggml_nelements(meta_tke); + n_bytes -= ggml_nbytes(meta_out); + n_elements -= ggml_nelements(meta_out); + if (n_bytes < GiB) { + LLAMA_LOG_INFO("%s: repeating layers = %.3f MiB (%.3f BPW", __func__, n_bytes/1024.0/1024.0, n_bytes*8.0/n_elements); + } else { + LLAMA_LOG_INFO("%s: repeating layers = %.3f GiB (%.3f BPW", __func__, n_bytes/1024.0/1024.0/1024.0, n_bytes*8.0/n_elements); + } + if (ml.n_elements >= 1e9) { + printf(", %.3f B parameters)\n", n_elements*1e-9); + } else { + printf(", %.3f M parameters)\n", n_elements*1e-6); + } + } } // general kv |