mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-10-31 08:51:55 +00:00
108 lines
3.1 KiB
C++
108 lines
3.1 KiB
C++
#include "common.h"
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#include "llama.h"
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#include "build-info.h"
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#include <ctime>
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int main(int argc, char ** argv) {
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gpt_params params;
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params.model = "models/llama-7B/ggml-model.bin";
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if (gpt_params_parse(argc, argv, params) == false) {
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return 1;
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}
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params.embedding = true;
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if (params.n_ctx > 2048) {
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fprintf(stderr, "%s: warning: model does not support context sizes greater than 2048 tokens (%d specified);"
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"expect poor results\n", __func__, params.n_ctx);
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}
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fprintf(stderr, "%s: build = %d (%s)\n", __func__, BUILD_NUMBER, BUILD_COMMIT);
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if (params.seed < 0) {
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params.seed = time(NULL);
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}
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fprintf(stderr, "%s: seed = %d\n", __func__, params.seed);
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std::mt19937 rng(params.seed);
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if (params.random_prompt) {
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params.prompt = gpt_random_prompt(rng);
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}
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llama_context * ctx;
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// load the model
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{
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auto lparams = llama_context_default_params();
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lparams.n_ctx = params.n_ctx;
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lparams.n_parts = params.n_parts;
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lparams.seed = params.seed;
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lparams.f16_kv = params.memory_f16;
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lparams.logits_all = params.perplexity;
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lparams.use_mmap = params.use_mmap;
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lparams.use_mlock = params.use_mlock;
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lparams.embedding = params.embedding;
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ctx = llama_init_from_file(params.model.c_str(), lparams);
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if (ctx == NULL) {
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fprintf(stderr, "%s: error: failed to load model '%s'\n", __func__, params.model.c_str());
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return 1;
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}
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}
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// print system information
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{
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fprintf(stderr, "\n");
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fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
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params.n_threads, std::thread::hardware_concurrency(), llama_print_system_info());
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}
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int n_past = 0;
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// Add a space in front of the first character to match OG llama tokenizer behavior
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params.prompt.insert(0, 1, ' ');
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// tokenize the prompt
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auto embd_inp = ::llama_tokenize(ctx, params.prompt, true);
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// determine newline token
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auto llama_token_newline = ::llama_tokenize(ctx, "\n", false);
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if (params.verbose_prompt) {
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fprintf(stderr, "\n");
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fprintf(stderr, "%s: prompt: '%s'\n", __func__, params.prompt.c_str());
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fprintf(stderr, "%s: number of tokens in prompt = %zu\n", __func__, embd_inp.size());
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for (int i = 0; i < (int) embd_inp.size(); i++) {
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fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], llama_token_to_str(ctx, embd_inp[i]));
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}
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fprintf(stderr, "\n");
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}
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if (params.embedding){
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if (embd_inp.size() > 0) {
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if (llama_eval(ctx, embd_inp.data(), embd_inp.size(), n_past, params.n_threads)) {
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fprintf(stderr, "%s : failed to eval\n", __func__);
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return 1;
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}
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}
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const int n_embd = llama_n_embd(ctx);
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const auto embeddings = llama_get_embeddings(ctx);
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for (int i = 0; i < n_embd; i++) {
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printf("%f ", embeddings[i]);
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}
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printf("\n");
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}
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llama_print_timings(ctx);
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llama_free(ctx);
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return 0;
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}
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