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synced 2025-11-07 09:57:00 +00:00
llama : refactor model loading code (#2620)
* llama : style formatting + remove helper methods * llama : fix quantization using gguf tool * llama : simplify gguf_file_saver * llama : fix method names * llama : simplify write_header() * llama : no need to pass full file loader to the file saver just gguf_ctx * llama : gguf_file_saver write I32 * llama : refactor tensor names (#2622) * gguf: update tensor names searched in quantization * gguf : define tensor names as constants * gguf : initial write API (not tested yet) * gguf : write to file API (not tested) * gguf : initial write API ready + example * gguf : fix header write * gguf : fixes + simplify example + add ggml_nbytes_pad() * gguf : minor * llama : replace gguf_file_saver with new gguf write API * gguf : streaming support when writing files * gguf : remove oboslete write methods * gguf : remove obosolete gguf_get_arr_xxx API * llama : simplify gguf_file_loader * llama : move hparams and vocab from gguf_file_loader to llama_model_loader * llama : merge gguf-util.h in llama.cpp * llama : reorder definitions in .cpp to match .h * llama : minor simplifications * llama : refactor llama_model_loader (WIP) wip : remove ggml_ctx from llama_model_loader wip : merge gguf_file_loader in llama_model_loader * llama : fix shape prints * llama : fix Windows build + fix norm_rms_eps key * llama : throw error on missing KV paris in model meta data * llama : improve printing + log meta data * llama : switch print order of meta data --------- Co-authored-by: M. Yusuf Sarıgöz <yusufsarigoz@gmail.com>
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@@ -74,7 +74,9 @@ int main(int argc, char ** argv) {
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// tokens (see "infinite text generation via context swapping" in the main example), but in this minimalist
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// example, we will just stop the loop once this cache is full or once an end of stream is detected.
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while (llama_get_kv_cache_token_count(ctx) < max_context_size) {
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const int n_gen = std::min(32, max_context_size);
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while (llama_get_kv_cache_token_count(ctx) < n_gen) {
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// evaluate the transformer
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if (llama_eval(ctx, tokens_list.data(), int(tokens_list.size()), llama_get_kv_cache_token_count(ctx), params.n_threads)) {
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@@ -114,7 +116,6 @@ int main(int argc, char ** argv) {
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// push this new token for next evaluation
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tokens_list.push_back(new_token_id);
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}
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llama_free(ctx);
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@@ -122,5 +123,7 @@ int main(int argc, char ** argv) {
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llama_backend_free();
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fprintf(stderr, "\n\n");
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return 0;
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}
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