aditya/llama.cpp
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cmdline option for custom amount of model parts (--n_parts N) (#348)

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* cmdline option for custom amount of model parts (--n_parts N)

* Update main.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
anzz1 2023-03-21 17:42:43 +02:00 committed by GitHub
parent e0ffc861fa
commit 975d2cebf9
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3 changed files with 12 additions and 5 deletions
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11
main.cpp
View file

@ -90,7 +90,8 @@ struct llama_model {
};
// load the model's weights from a file
bool llama_model_load(const std::string & fname, llama_model & model, llama_vocab & vocab, int n_ctx, ggml_type memory_type = GGML_TYPE_F32) {
bool llama_model_load(const std::string & fname, llama_model & model, llama_vocab & vocab, int n_ctx, int n_parts, ggml_type memory_type = GGML_TYPE_F32) {
fprintf(stderr, "%s: loading model from '%s' - please wait ...\n", __func__, fname.c_str());
std::vector<char> f_buf(1024*1024);
@ -127,7 +128,6 @@ bool llama_model_load(const std::string & fname, llama_model & model, llama_voca
}
int n_ff = 0;
int n_parts = 0;
// load hparams
{
@ -145,7 +145,10 @@ bool llama_model_load(const std::string & fname, llama_model & model, llama_voca
hparams.n_ctx = n_ctx;
n_ff = ((2*(4*hparams.n_embd)/3 + hparams.n_mult - 1)/hparams.n_mult)*hparams.n_mult;
n_parts = LLAMA_N_PARTS.at(hparams.n_embd);
if (n_parts < 1) {
n_parts = LLAMA_N_PARTS.at(hparams.n_embd);
}
fprintf(stderr, "%s: n_vocab = %d\n", __func__, hparams.n_vocab);
fprintf(stderr, "%s: n_ctx = %d\n", __func__, hparams.n_ctx);
@ -839,7 +842,7 @@ int main(int argc, char ** argv) {
{
const ggml_type memory_type = params.memory_f16 ? GGML_TYPE_F16 : GGML_TYPE_F32;
const int64_t t_start_us = ggml_time_us();
if (!llama_model_load(params.model, model, vocab, params.n_ctx, memory_type)) {
if (!llama_model_load(params.model, model, vocab, params.n_ctx, params.n_parts, memory_type)) {
fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, params.model.c_str());
return 1;
}

3
utils.cpp
View file

@ -74,6 +74,8 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
params.antiprompt.push_back(argv[++i]);
} else if (arg == "--ignore-eos") {
params.ignore_eos = true;
} else if (arg == "--n_parts") {
params.n_parts = std::stoi(argv[++i]);
} else if (arg == "-h" || arg == "--help") {
gpt_print_usage(argc, argv, params);
exit(0);
@ -116,6 +118,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, " --ignore-eos ignore end of stream token and continue generating\n");
fprintf(stderr, " --memory_f16 use f16 instead of f32 for memory key+value\n");
fprintf(stderr, " --temp N temperature (default: %.1f)\n", params.temp);
fprintf(stderr, " --n_parts N number of model parts (default: -1 = determine from dimensions)\n");
fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(stderr, " -m FNAME, --model FNAME\n");
fprintf(stderr, " model path (default: %s)\n", params.model.c_str());

3
utils.h
View file

@ -13,10 +13,11 @@
//
struct gpt_params {
int32_t seed = -1; // RNG seed
int32_t seed = -1; // RNG seed
int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
int32_t n_predict = 128; // new tokens to predict
int32_t repeat_last_n = 64; // last n tokens to penalize
int32_t n_parts = -1; // amount of model parts (-1 = determine from model dimensions)
int32_t n_ctx = 512; //context size
// sampling parameters