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common : add HF arg helpers
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@ -647,14 +647,6 @@ static bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg,
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params.model = argv[i];
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return true;
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}
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if (arg == "-mu" || arg == "--model-url") {
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if (++i >= argc) {
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invalid_param = true;
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return true;
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}
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params.model_url = argv[i];
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return true;
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}
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if (arg == "-md" || arg == "--model-draft") {
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if (++i >= argc) {
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invalid_param = true;
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@ -671,6 +663,30 @@ static bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg,
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params.model_alias = argv[i];
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return true;
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}
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if (arg == "-mu" || arg == "--model-url") {
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if (++i >= argc) {
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invalid_param = true;
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return true;
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}
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params.model_url = argv[i];
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return true;
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}
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if (arg == "-hfr" || arg == "--hf-repo") {
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if (++i >= argc) {
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invalid_param = true;
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return true;
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}
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params.hf_repo = argv[i];
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return true;
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}
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if (arg == "-hff" || arg == "--hf-file") {
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if (++i >= argc) {
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invalid_param = true;
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return true;
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}
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params.hf_file = argv[i];
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return true;
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}
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if (arg == "--lora") {
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if (++i >= argc) {
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invalid_param = true;
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@ -1403,10 +1419,14 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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printf(" layer range to apply the control vector(s) to, start and end inclusive\n");
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printf(" -m FNAME, --model FNAME\n");
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printf(" model path (default: %s)\n", params.model.c_str());
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printf(" -mu MODEL_URL, --model-url MODEL_URL\n");
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printf(" model download url (default: %s)\n", params.model_url.c_str());
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printf(" -md FNAME, --model-draft FNAME\n");
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printf(" draft model for speculative decoding\n");
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printf(" -mu MODEL_URL, --model-url MODEL_URL\n");
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printf(" model download url (default: %s)\n", params.model_url.c_str());
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printf(" -hfr REPO, --hf-repo REPO\n");
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printf(" Hugging Face model repository (default: %s)\n", params.hf_repo.c_str());
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printf(" -hff FILE, --hf-file FILE\n");
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printf(" Hugging Face model file (default: %s)\n", params.hf_file.c_str());
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printf(" -ld LOGDIR, --logdir LOGDIR\n");
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printf(" path under which to save YAML logs (no logging if unset)\n");
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printf(" --override-kv KEY=TYPE:VALUE\n");
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@ -1655,8 +1675,10 @@ void llama_batch_add(
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#ifdef LLAMA_USE_CURL
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struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model,
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struct llama_model_params params) {
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struct llama_model * llama_load_model_from_url(
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const char * model_url,
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const char * path_model,
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const struct llama_model_params & params) {
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// Basic validation of the model_url
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if (!model_url || strlen(model_url) == 0) {
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fprintf(stderr, "%s: invalid model_url\n", __func__);
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@ -1850,25 +1872,62 @@ struct llama_model * llama_load_model_from_url(const char * model_url, const cha
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return llama_load_model_from_file(path_model, params);
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}
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struct llama_model * llama_load_model_from_hf(
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const char * repo,
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const char * model,
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const char * path_model,
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const struct llama_model_params & params) {
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// construct hugging face model url:
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//
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// --repo ggml-org/models --file tinyllama-1.1b/ggml-model-f16.gguf
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// https://huggingface.co/ggml-org/models/resolve/main/tinyllama-1.1b/ggml-model-f16.gguf
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//
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// --repo TheBloke/Mixtral-8x7B-v0.1-GGUF --file mixtral-8x7b-v0.1.Q4_K_M.gguf
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// https://huggingface.co/TheBloke/Mixtral-8x7B-v0.1-GGUF/resolve/main/mixtral-8x7b-v0.1.Q4_K_M.gguf
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//
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std::string model_url = "https://huggingface.co/";
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model_url += repo;
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model_url += "/resolve/main/";
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model_url += model;
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return llama_load_model_from_url(model_url.c_str(), path_model, params);
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}
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#else
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struct llama_model * llama_load_model_from_url(const char * /*model_url*/, const char * /*path_model*/,
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struct llama_model_params /*params*/) {
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struct llama_model * llama_load_model_from_url(
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const char * /*model_url*/,
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const char * /*path_model*/,
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const struct llama_model_params & /*params*/) {
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fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from an url not supported.\n", __func__);
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return nullptr;
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}
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struct llama_model * llama_load_model_from_hf(
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const char * /*repo*/,
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const char * /*model*/,
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const char * /*path_model*/,
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const struct llama_model_params & /*params*/) {
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fprintf(stderr, "%s: llama.cpp built without libcurl, downloading from Hugging Face not supported.\n", __func__);
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return nullptr;
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}
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#endif // LLAMA_USE_CURL
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std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_params(gpt_params & params) {
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auto mparams = llama_model_params_from_gpt_params(params);
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llama_model * model = nullptr;
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if (!params.model_url.empty()) {
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if (!params.hf_repo.empty() && !params.hf_file.empty()) {
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model = llama_load_model_from_hf(params.hf_repo.c_str(), params.hf_file.c_str(), params.model.c_str(), mparams);
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} else if (!params.model_url.empty()) {
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model = llama_load_model_from_url(params.model_url.c_str(), params.model.c_str(), mparams);
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} else {
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model = llama_load_model_from_file(params.model.c_str(), mparams);
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}
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if (model == 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 std::make_tuple(nullptr, nullptr);
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@ -1908,7 +1967,7 @@ std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_par
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}
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for (unsigned int i = 0; i < params.lora_adapter.size(); ++i) {
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const std::string& lora_adapter = std::get<0>(params.lora_adapter[i]);
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const std::string & lora_adapter = std::get<0>(params.lora_adapter[i]);
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float lora_scale = std::get<1>(params.lora_adapter[i]);
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int err = llama_model_apply_lora_from_file(model,
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lora_adapter.c_str(),
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@ -89,9 +89,11 @@ struct gpt_params {
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struct llama_sampling_params sparams;
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std::string model = "models/7B/ggml-model-f16.gguf"; // model path
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std::string model_url = ""; // model url to download
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std::string model_draft = ""; // draft model for speculative decoding
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std::string model_draft = ""; // draft model for speculative decoding
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std::string model_alias = "unknown"; // model alias
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std::string model_url = ""; // model url to download
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std::string hf_repo = ""; // HF repo
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std::string hf_file = ""; // HF file
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std::string prompt = "";
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std::string prompt_file = ""; // store the external prompt file name
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std::string path_prompt_cache = ""; // path to file for saving/loading prompt eval state
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@ -192,8 +194,8 @@ std::tuple<struct llama_model *, struct llama_context *> llama_init_from_gpt_par
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struct llama_model_params llama_model_params_from_gpt_params (const gpt_params & params);
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struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params);
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struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model,
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struct llama_model_params params);
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struct llama_model * llama_load_model_from_url(const char * model_url, const char * path_model, const struct llama_model_params & params);
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struct llama_model * llama_load_model_from_hf(const char * repo, const char * file, const char * path_model, const struct llama_model_params & params);
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// Batch utils
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