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	llama.cpp : split llama_context_params into model and context params (#3301)
* llama.cpp : split llama_context_params into model and context params ggml-ci * fix metal build * fix freq_base/scale default to model value * llama-bench : keep the same model between tests when possible * move n_threads to llama_context_params, add n_threads_batch * fix mpi build * remove kv_size(), cuda scratch fixes * remove low-vram option * add n_threads_batch to system info, refactor to get_system_info() * add documentation about --threads-batch to the READMEs * llama-bench fix * main : fix rope freq/scale warning * llama.cpp : add llama_get_model common : add llama_tokenize from model * remove duplicated ctx/model functions ggml-ci * cuda : print total VRAM used
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		@@ -62,18 +62,20 @@ int main(int argc, char **argv) {
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    // load the vocab
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    {
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        auto lparams = llama_context_default_params();
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        auto mparams = llama_model_default_params();
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        lparams.vocab_only = true;
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        mparams.vocab_only = true;
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        model = llama_load_model_from_file(fname.c_str(), lparams);
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        model = llama_load_model_from_file(fname.c_str(), mparams);
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        if (model == NULL) {
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            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
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            return 1;
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        }
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        ctx = llama_new_context_with_model(model, lparams);
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        auto cparams = llama_context_default_params();
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        ctx = llama_new_context_with_model(model, cparams);
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        if (ctx == NULL) {
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            fprintf(stderr, "%s: error: failed to load vocab '%s'\n", __func__, fname.c_str());
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@@ -82,7 +84,7 @@ int main(int argc, char **argv) {
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        }
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    }
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    if (llama_vocab_type(ctx) != LLAMA_VOCAB_TYPE_BPE) {
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    if (llama_vocab_type(model) != LLAMA_VOCAB_TYPE_BPE) {
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        fprintf(stderr, "%s : error: vocab type is not SPM\n", __func__);
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        llama_free_model(model);
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        llama_free(ctx);
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