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