mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-10-31 23:28:51 +01:00
1b67731e18
Key changes: * BERT conversion: fix abuse of LlamaHfVocab, do not set BOS or EOS * Nomic Embed conversion: pad vocab instead of slicing embedding tensor * llama_tokenize: handle added special tokens like HF does
42 lines
1.1 KiB
C++
42 lines
1.1 KiB
C++
#include "ggml.h"
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#include "llama.h"
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#include "common.h"
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#include "ngram-cache.h"
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#include <cstdint>
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#include <fstream>
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#include <iostream>
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#include <string>
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#include <unordered_map>
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#include <vector>
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int main(int argc, char ** argv){
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gpt_params params;
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if (!gpt_params_parse(argc, argv, params)) {
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return 1;
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}
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// init llama.cpp
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llama_backend_init();
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llama_numa_init(params.numa);
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llama_model * model = NULL;
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llama_context * ctx = NULL;
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// load the model
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std::tie(model, ctx) = llama_init_from_gpt_params(params);
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GGML_ASSERT(model != nullptr);
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// tokenize the prompt
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std::vector<llama_token> inp;
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inp = ::llama_tokenize(ctx, params.prompt, true, true);
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fprintf(stderr, "%s: tokenization done\n", __func__);
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llama_ngram_cache ngram_cache;
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llama_ngram_cache_update(ngram_cache, LLAMA_NGRAM_STATIC, LLAMA_NGRAM_STATIC, inp, inp.size(), true);
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fprintf(stderr, "%s: hashing done, writing file to %s\n", __func__, params.lookup_cache_static.c_str());
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llama_ngram_cache_save(ngram_cache, params.lookup_cache_static);
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}
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