diff --git a/main.cpp b/main.cpp index 6dc9ae980..9bbdd1153 100644 --- a/main.cpp +++ b/main.cpp @@ -818,8 +818,7 @@ int main(int argc, char ** argv) { // load the model { const int64_t t_start_us = ggml_time_us(); - - if (!llama_model_load(params.model, model, vocab, 512)) { // TODO: set context from user input ?? + if (!llama_model_load(params.model, model, vocab, params.n_ctx)) { fprintf(stderr, "%s: failed to load model from '%s'\n", __func__, params.model.c_str()); return 1; } diff --git a/utils.cpp b/utils.cpp index 54217f02f..189ec231c 100644 --- a/utils.cpp +++ b/utils.cpp @@ -37,7 +37,9 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) { params.n_predict = std::stoi(argv[++i]); } else if (arg == "--top_k") { params.top_k = std::stoi(argv[++i]); - } else if (arg == "--top_p") { + } else if (arg == "-c" || arg == "--ctx_size") { + params.n_ctx = std::stoi(argv[++i]); + } else if (arg == "--top_p") { params.top_p = std::stof(argv[++i]); } else if (arg == "--temp") { params.temp = std::stof(argv[++i]); @@ -92,6 +94,7 @@ void gpt_print_usage(int argc, char ** argv, const gpt_params & params) { fprintf(stderr, " --top_p N top-p sampling (default: %.1f)\n", params.top_p); fprintf(stderr, " --repeat_last_n N last n tokens to consider for penalize (default: %d)\n", params.repeat_last_n); fprintf(stderr, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f)\n", params.repeat_penalty); + fprintf(stderr, " -c N, --ctx_size N size of the prompt context (default: %d)\n", params.n_ctx); fprintf(stderr, " --temp N temperature (default: %.1f)\n", params.temp); 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"); diff --git a/utils.h b/utils.h index 4f98011cf..36c1153e6 100644 --- a/utils.h +++ b/utils.h @@ -17,7 +17,7 @@ struct gpt_params { 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_ctx = 512; //context size // sampling parameters int32_t top_k = 40; float top_p = 0.95f;