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massive refactor completed, GPT-J integrated

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Concedo 2023-04-02 17:03:30 +08:00
parent b1f08813e3
commit 9aabb0d9db
21 changed files with 3979 additions and 5054 deletions
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11
llama_adapter.cpp
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@ -12,6 +12,9 @@
#include "ggml.h"
#include "model_adapter.h"
//for easier compilation
#include "llamaextra.cpp"
//return val: 0=fail, 1=(original ggml, alpaca), 2=(ggmf), 3=(ggjt)
static FileFormat file_format = FileFormat::FAIL;
static llama_context_params ctx_params;
@ -109,7 +112,6 @@ generation_outputs llama_generate(const generation_inputs inputs, generation_out
embd_inp = ::llama_tokenize(ctx, params.prompt, true);
}
//params.n_predict = std::min(params.n_predict, params.n_ctx - (int) embd_inp.size());
//truncate to front of the prompt if its too long
if (embd_inp.size() + params.n_predict > params.n_ctx)
{
@ -124,11 +126,6 @@ generation_outputs llama_generate(const generation_inputs inputs, generation_out
int last_n_size = params.repeat_last_n;
last_n_tokens.resize(last_n_size);
//display usage
// std::string tst = " ";
// char * tst2 = (char*)tst.c_str();
// gpt_print_usage(1,&tst2,params);
std::fill(last_n_tokens.begin(), last_n_tokens.end(), 0);
n_past = 0;
@ -194,7 +191,7 @@ generation_outputs llama_generate(const generation_inputs inputs, generation_out
{
printf("\rGenerating (%d / %d tokens)", (1 + params.n_predict - remaining_tokens), params.n_predict);
}
//printf("\nnp:%d embd:%d txt:%s",n_past,embd.size(),llama_token_to_str(ctx, embd[0]));
if (llama_eval(ctx, embd.data(), embdsize, n_past, params.n_threads))
{
fprintf(stderr, "Failed to predict\n");