--- /dev/null
+#include "arg.h"
+#include "common.h"
+#include "download.h"
+#include "log.h"
+
+#include <cstdio>
+#include <filesystem>
+
+static void print_usage(int /*argc*/, char ** argv) {
+ printf(
+ "\nexamples:\n"
+ " %s -hf ggml-org/gemma-3-4b-it-qat-GGUF\n"
+ " %s -hf ggml-org/gemma-3-4b-it-qat-GGUF:Q4_K_M\n"
+ " %s -hf ggml-org/models -hff model.gguf\n"
+ " %s -mu https://example.com/model.gguf -m model.gguf\n"
+ "\n",
+ argv[0], argv[0], argv[0], argv[0]
+ );
+}
+
+int llama_download(int argc, char ** argv);
+
+int llama_download(int argc, char ** argv) {
+ common_init();
+
+ common_params params;
+ params.verbosity = LOG_LEVEL_ERROR;
+
+ if (!common_params_parse(argc, argv, params, LLAMA_EXAMPLE_DOWNLOAD, print_usage)) {
+ return 1;
+ }
+
+ const bool has_source = !params.model.hf_repo.empty() || !params.model.url.empty() ||
+ !params.model.path.empty() || !params.model.docker_repo.empty();
+ if (!has_source) {
+ fprintf(stderr, "error: no model source specified (use --hf-repo, --model-url, --model or --docker-repo)\n");
+ return 1;
+ }
+
+ try {
+ common_params_handle_models(params, LLAMA_EXAMPLE_DOWNLOAD, {});
+ } catch (const std::exception & e) {
+ fprintf(stderr, "error: %s\n", e.what());
+ return 1;
+ }
+
+ if (!params.models_preset.empty()) {
+ // -hf pointed at a preset repo: print the preset path and stop
+ printf("%s\n", params.models_preset.c_str());
+ return 0;
+ }
+ if (params.model.path.empty()) {
+ fprintf(stderr, "error: model download failed\n");
+ return 1;
+ }
+ if (!std::filesystem::exists(params.model.path)) {
+ fprintf(stderr, "error: model file does not exist: %s\n", params.model.path.c_str());
+ return 1;
+ }
+
+ printf("%s\n", params.model.path.c_str());
+ if (!params.mmproj.path.empty()) {
+ printf("%s\n", params.mmproj.path.c_str());
+ }
+ if (!params.speculative.draft.mparams.path.empty()) {
+ printf("%s\n", params.speculative.draft.mparams.path.c_str());
+ }
+
+ return 0;
+}
int llama_fit_params(int argc, char ** argv);
int llama_quantize(int argc, char ** argv);
int llama_perplexity(int argc, char ** argv);
+int llama_download(int argc, char ** argv);
// Self-update is only supported for binaries built with llama-install.sh
static int llama_update(int argc, char ** argv) {
{"serve", "HTTP API server", {"server"}, false, llama_server },
{"cli", "Command-line interactive interface", {"client"}, false, llama_cli },
{"update", "Update llama to the latest release", {}, UPDATE_HIDDEN, llama_update },
+ {"download", "Download a model", {"get"}, false, llama_download },
{"completion", "Text completion", {"complete"}, true, llama_completion },
{"bench", "Benchmark prompt processing and text generation", {}, true, llama_bench },
{"batched-bench", "Benchmark batched decoding performance", {}, true, llama_batched_bench},
const bool skip_model_download =
// server will call common_params_handle_models() later, so we skip it here
ctx_arg.ex == LLAMA_EXAMPLE_SERVER ||
+ // download calls common_params_handle_models() itself and prints the paths
+ ctx_arg.ex == LLAMA_EXAMPLE_DOWNLOAD ||
// export_graph_ops loads only metadata
ctx_arg.ex == LLAMA_EXAMPLE_EXPORT_GRAPH_OPS;
common_options.push_back(&opt);
}
}
- printf("----- common params -----\n\n");
- print_options(common_options);
- printf("\n\n----- sampling params -----\n\n");
- print_options(sampling_options);
- printf("\n\n----- speculative params -----\n\n");
- print_options(spec_options);
- // TODO: maybe convert enum llama_example to string
- printf("\n\n----- example-specific params -----\n\n");
- print_options(specific_options);
+ bool first = true;
+ auto print_section = [&](const char * header, std::vector<common_arg *> & options) {
+ if (options.empty()) {
+ return;
+ }
+ printf("%s----- %s -----\n\n", first ? "" : "\n\n", header);
+ first = false;
+ print_options(options);
+ };
+ print_section("common params", common_options);
+ print_section("sampling params", sampling_options);
+ print_section("speculative params", spec_options);
+ print_section("example-specific params", specific_options);
}
static void common_params_print_completion(common_params_context & ctx_arg) {
* - if both {LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_*,} are set, we will prioritize the LLAMA_EXAMPLE_* matching current example
*/
auto add_opt = [&](common_arg arg) {
- if ((arg.in_example(ex) || arg.in_example(LLAMA_EXAMPLE_COMMON)) && !arg.is_exclude(ex)) {
+ // download only exposes the handful of args explicitly tagged for it
+ const bool inherit_common = ex != LLAMA_EXAMPLE_DOWNLOAD;
+ if ((arg.in_example(ex) || (inherit_common && arg.in_example(LLAMA_EXAMPLE_COMMON))) && !arg.is_exclude(ex)) {
ctx_arg.options.push_back(std::move(arg));
}
};
[](common_params & params) {
params.usage = true;
}
- ));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}));
add_opt(common_arg(
{"--version"},
"show version and build info",
[](common_params & params, bool value) {
params.no_mmproj = !value;
}
- ).set_examples(mmproj_examples).set_env("LLAMA_ARG_MMPROJ_AUTO"));
+ ).set_examples({LLAMA_EXAMPLE_MTMD, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_MMPROJ_AUTO"));
add_opt(common_arg(
{"--mmproj-offload"},
{"--no-mmproj-offload"},
[](common_params & params, const std::string & value) {
params.model.path = value;
}
- ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_EXPORT_LORA}).set_env("LLAMA_ARG_MODEL"));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_EXPORT_LORA, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_MODEL"));
add_opt(common_arg(
{"-mu", "--model-url"}, "MODEL_URL",
"model download url (default: unused)",
[](common_params & params, const std::string & value) {
params.model.url = value;
}
- ).set_env("LLAMA_ARG_MODEL_URL"));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_MODEL_URL"));
add_opt(common_arg(
{ "-dr", "--docker-repo" }, "[<repo>/]<model>[:quant]",
"Docker Hub model repository. repo is optional, default to ai/. quant is optional, default to :latest.\n"
[](common_params & params, const std::string & value) {
params.model.docker_repo = value;
}
- ).set_env("LLAMA_ARG_DOCKER_REPO"));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_DOCKER_REPO"));
add_opt(common_arg(
{"-hf", "-hfr", "--hf-repo"}, "<user>/<model>[:quant]",
"Hugging Face model repository; quant is optional, case-insensitive, default to Q4_K_M, or falls back to the first file in the repo if Q4_K_M doesn't exist.\n"
[](common_params & params, const std::string & value) {
params.model.hf_repo = value;
}
- ).set_env("LLAMA_ARG_HF_REPO"));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_HF_REPO"));
add_opt(common_arg(
{"-hff", "--hf-file"}, "FILE",
"Hugging Face model file. If specified, it will override the quant in --hf-repo (default: unused)",
[](common_params & params, const std::string & value) {
params.model.hf_file = value;
}
- ).set_env("LLAMA_ARG_HF_FILE"));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("LLAMA_ARG_HF_FILE"));
add_opt(common_arg(
{"-hfv", "-hfrv", "--hf-repo-v"}, "<user>/<model>[:quant]",
"Hugging Face model repository for the vocoder model (default: unused)",
[](common_params & params, const std::string & value) {
params.hf_token = value;
}
- ).set_env("HF_TOKEN"));
+ ).set_examples({LLAMA_EXAMPLE_COMMON, LLAMA_EXAMPLE_DOWNLOAD}).set_env("HF_TOKEN"));
+ add_opt(common_arg(
+ {"--mtp"},
+ "also download the multi-token prediction (MTP) head, if available (default: unused)",
+ [](common_params & params) {
+ params.speculative.types.push_back(COMMON_SPECULATIVE_TYPE_DRAFT_MTP);
+ }
+ ).set_examples({LLAMA_EXAMPLE_DOWNLOAD}));
add_opt(common_arg(
{"--context-file"}, "FNAME",
"file to load context from (use comma-separated values to specify multiple files)",
overview / pkg / ggml / sources / llama.cpp / commitdiff