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https://github.com/ggerganov/llama.cpp.git
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Fix bool return in llama_model_load, remove std::ignore use
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@ -3700,7 +3700,7 @@ static bool llm_load_tensors(
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return ok;
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return ok;
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}
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}
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// Returns -1 on error, -2 on cancellation via llama_progress_callback
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// Returns 0 on success, -1 on error, and -2 on cancellation via llama_progress_callback
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static int llama_model_load(const std::string & fname, llama_model & model, const llama_model_params & params) {
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static int llama_model_load(const std::string & fname, llama_model & model, const llama_model_params & params) {
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try {
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try {
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llama_model_loader ml(fname, params.use_mmap, params.kv_overrides);
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llama_model_loader ml(fname, params.use_mmap, params.kv_overrides);
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@ -3719,7 +3719,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, cons
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if (params.vocab_only) {
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if (params.vocab_only) {
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LLAMA_LOG_INFO("%s: vocab only - skipping tensors\n", __func__);
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LLAMA_LOG_INFO("%s: vocab only - skipping tensors\n", __func__);
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return true;
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return 0;
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}
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}
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if (!llm_load_tensors(
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if (!llm_load_tensors(
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@ -1,17 +1,16 @@
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#include "llama.h"
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#include "llama.h"
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#include <cstdlib>
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#include <cstdlib>
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#include <tuple>
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int main(void) {
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int main(void) {
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llama_backend_init(false);
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llama_backend_init(false);
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auto params = llama_model_params{};
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auto params = llama_model_params{};
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params.use_mmap = false;
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params.use_mmap = false;
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params.progress_callback = [](float progress, void * ctx){
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params.progress_callback = [](float progress, void * ctx){
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std::ignore = ctx;
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(void) ctx;
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return progress > 0.50;
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return progress > 0.50;
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};
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};
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auto * model = llama_load_model_from_file("../models/7B/ggml-model-f16.gguf", params);
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auto * model = llama_load_model_from_file("models/7B/ggml-model-f16.gguf", params);
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llama_backend_free();
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llama_backend_free();
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return model == nullptr ? EXIT_SUCCESS : EXIT_FAILURE;
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return model == nullptr ? EXIT_SUCCESS : EXIT_FAILURE;
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}
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}
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