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llama.cpp : print kv general.name
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d9e6890a51
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11
llama.cpp
11
llama.cpp
@ -1329,6 +1329,8 @@ static void llama_model_load_internal(
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auto & hparams = model.hparams;
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std::string general_name = "n/a";
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// read hparams
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{
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struct gguf_context * ctx = ml->ctx_gguf;
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@ -1347,6 +1349,10 @@ static void llama_model_load_internal(
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} \
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}
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// get general kv
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GGUF_GET(general_name, gguf_get_val_str, GGUF_TYPE_STRING, false, "general.name");
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// get hparams kv
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GGUF_GET(hparams.n_vocab, gguf_get_arr_n, GGUF_TYPE_ARRAY, true, "tokenizer.ggml.tokens");
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GGUF_GET(hparams.n_ctx_train, gguf_get_val_u32, GGUF_TYPE_UINT32, true, "llama.context_length");
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GGUF_GET(hparams.n_embd, gguf_get_val_u32, GGUF_TYPE_UINT32, true, "llama.embedding_length");
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@ -1359,6 +1365,7 @@ static void llama_model_load_internal(
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// n_head_kv is optional, default to n_head
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hparams.n_head_kv = hparams.n_head;
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GGUF_GET(hparams.n_head_kv, gguf_get_val_u32, GGUF_TYPE_UINT32, false, "llama.attention.head_count_kv");
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#undef GGUF_GET
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switch (hparams.n_layer) {
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@ -1422,6 +1429,8 @@ static void llama_model_load_internal(
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}
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{
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LLAMA_LOG_INFO("%s: general.name = %s\n", __func__, general_name.c_str());
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LLAMA_LOG_INFO("%s: format = %s\n", __func__, llama_file_version_name(ml->file_version));
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LLAMA_LOG_INFO("%s: n_vocab = %u\n", __func__, hparams.n_vocab);
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LLAMA_LOG_INFO("%s: n_ctx_train = %u\n", __func__, hparams.n_ctx_train);
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@ -1437,7 +1446,7 @@ static void llama_model_load_internal(
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LLAMA_LOG_INFO("%s: freq_base = %.1f\n", __func__, hparams.rope_freq_base);
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LLAMA_LOG_INFO("%s: freq_scale = %g\n", __func__, hparams.rope_freq_scale);
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LLAMA_LOG_INFO("%s: model type = %s\n", __func__, llama_model_type_name(model.type));
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LLAMA_LOG_INFO("%s: model size = %.2fB\n", __func__, ml->n_elements*1e-9);
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LLAMA_LOG_INFO("%s: model size = %.2f B\n", __func__, ml->n_elements*1e-9);
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// TODO: print number of tensors for each quantization
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}
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