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#include "llm.h" |
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#include "llms/dolly.cc" |
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#include "llms/gpt-neox.cc" |
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#include "llms/gpt2.cc" |
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#include "llms/gptj.cc" |
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#include "llms/llama.cc" |
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#include "llms/mpt.cc" |
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#include "llms/replit.cc" |
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#include "llms/starcoder.cc" |
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#include "llms/falcon.cc" |
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#ifdef __cplusplus |
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extern "C" { |
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#endif |
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LLM* ctransformers_llm_create(const char* model_path, const char* model_type, |
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const int context_length, const int gpu_layers) { |
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std::string type = model_type; |
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type.erase(std::remove_if(type.begin(), type.end(), |
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[](const char c) { return !std::isalnum(c); }), |
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type.end()); |
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LLM* llm = nullptr; |
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if (type == "dollyv2") { |
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llm = new dollyv2_llm; |
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} else if (type == "falcon") { |
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llm = new falcon_llm; |
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} else if (type == "gpt2") { |
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llm = new gpt2_llm; |
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} else if (type == "gptj") { |
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llm = new gptj_llm; |
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} else if (type == "gptneox") { |
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llm = new gpt_neox_llm; |
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} else if (type == "llama") { |
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llm = new llama_llm; |
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} else if (type == "mpt") { |
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llm = new mpt_llm; |
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} else if (type == "replit") { |
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llm = new replit_llm; |
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} else if (type == "starcoder") { |
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llm = new starcoder_llm; |
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} |
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if (llm == nullptr) { |
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fprintf(stderr, "Model type '%s' is not supported.\n", model_type); |
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return nullptr; |
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} |
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if (!llm->Init(model_path, context_length, gpu_layers)) { |
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delete llm; |
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return nullptr; |
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} |
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return llm; |
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} |
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void ctransformers_llm_delete(LLM* llm) { delete llm; } |
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int ctransformers_llm_tokenize(LLM* llm, const char* text, int* output) { |
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const std::vector<gpt_vocab::id> tokens = llm->Tokenize(text); |
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std::copy(tokens.begin(), tokens.end(), output); |
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return tokens.size(); |
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} |
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const char* ctransformers_llm_detokenize(LLM* llm, const int token) { |
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return llm->Detokenize(token).c_str(); |
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} |
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bool ctransformers_llm_is_eos_token(LLM* llm, const int token) { |
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return llm->IsEosToken(token); |
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} |
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int ctransformers_llm_eos_token_id(LLM* llm) { return llm->EosToken(); } |
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int ctransformers_llm_vocab_size(LLM* llm) { return llm->VocabSize(); } |
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int ctransformers_llm_context_length(LLM* llm) { return llm->ContextLength(); } |
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bool ctransformers_llm_batch_eval(LLM* llm, const int* tokens, |
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const int n_tokens, const int batch_size, |
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const int threads) { |
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return llm->BatchEval(std::vector<gpt_vocab::id>(tokens, tokens + n_tokens), |
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batch_size, threads); |
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} |
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float* ctransformers_llm_logits_data(LLM* llm) { return llm->Logits().data(); } |
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int ctransformers_llm_logits_size(LLM* llm) { return llm->Logits().size(); } |
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const float* ctransformers_llm_embeddings_data(LLM* llm) { |
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return llm->Embeddings().data(); |
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} |
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int ctransformers_llm_embeddings_size(LLM* llm) { |
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return llm->Embeddings().size(); |
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} |
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int ctransformers_llm_sample(LLM* llm, const int top_k, const float top_p, |
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const float temperature, |
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const float repetition_penalty, |
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const int last_n_tokens, const int seed) { |
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return llm->Sample(top_k, top_p, temperature, repetition_penalty, |
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last_n_tokens, seed); |
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} |
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void ctransformers_llm_reset(LLM* llm) { llm->Reset(); } |
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#ifdef __cplusplus |
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} |
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#endif |
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