llama : improve infill support and special token detection (#9798)
* llama : improve infill support ggml-ci * llama : add more FIM token strings ggml-ci * server : update prompt on slot restore (#9800) * gguf : deprecate old FIM token KVs
This commit is contained in:
Georgi Gerganov
GitHub
parent
943d20b411
commit
11ac9800af
12 changed files with 601 additions and 427 deletions
248
common/arg.cpp
248
common/arg.cpp
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@ -119,32 +119,6 @@ std::string common_arg::to_string() {
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// utils
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//
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#ifdef __GNUC__
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#ifdef __MINGW32__
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#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
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#else
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#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
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#endif
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#else
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#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...)
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#endif
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LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
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static std::string format(const char * fmt, ...) {
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va_list ap;
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va_list ap2;
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va_start(ap, fmt);
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va_copy(ap2, ap);
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int size = vsnprintf(NULL, 0, fmt, ap);
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GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT
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std::vector<char> buf(size + 1);
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int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2);
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GGML_ASSERT(size2 == size);
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va_end(ap2);
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va_end(ap);
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return std::string(buf.data(), size);
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}
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static void common_params_handle_model_default(common_params & params) {
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if (!params.hf_repo.empty()) {
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// short-hand to avoid specifying --hf-file -> default it to --model
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@ -199,7 +173,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
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continue;
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}
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} catch (std::exception & e) {
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throw std::invalid_argument(format(
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throw std::invalid_argument(string_format(
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"error while handling environment variable \"%s\": %s\n\n", opt.env, e.what()));
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}
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}
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@ -220,7 +194,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
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std::replace(arg.begin(), arg.end(), '_', '-');
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}
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if (arg_to_options.find(arg) == arg_to_options.end()) {
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throw std::invalid_argument(format("error: invalid argument: %s", arg.c_str()));
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throw std::invalid_argument(string_format("error: invalid argument: %s", arg.c_str()));
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}
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auto opt = *arg_to_options[arg];
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if (opt.has_value_from_env()) {
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@ -252,7 +226,7 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
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continue;
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}
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} catch (std::exception & e) {
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throw std::invalid_argument(format(
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throw std::invalid_argument(string_format(
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"error while handling argument \"%s\": %s\n\n"
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"usage:\n%s\n\nto show complete usage, run with -h",
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arg.c_str(), e.what(), arg_to_options[arg]->to_string().c_str()));
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@ -391,28 +365,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"--verbose-prompt"},
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format("print a verbose prompt before generation (default: %s)", params.verbose_prompt ? "true" : "false"),
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string_format("print a verbose prompt before generation (default: %s)", params.verbose_prompt ? "true" : "false"),
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[](common_params & params) {
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params.verbose_prompt = true;
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}
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));
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add_opt(common_arg(
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{"--no-display-prompt"},
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format("don't print prompt at generation (default: %s)", !params.display_prompt ? "true" : "false"),
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string_format("don't print prompt at generation (default: %s)", !params.display_prompt ? "true" : "false"),
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[](common_params & params) {
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params.display_prompt = false;
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}
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).set_examples({LLAMA_EXAMPLE_MAIN}));
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add_opt(common_arg(
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{"-co", "--color"},
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format("colorise output to distinguish prompt and user input from generations (default: %s)", params.use_color ? "true" : "false"),
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string_format("colorise output to distinguish prompt and user input from generations (default: %s)", params.use_color ? "true" : "false"),
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[](common_params & params) {
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params.use_color = true;
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}
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).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_INFILL, LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
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add_opt(common_arg(
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{"-t", "--threads"}, "N",
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format("number of threads to use during generation (default: %d)", params.cpuparams.n_threads),
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string_format("number of threads to use during generation (default: %d)", params.cpuparams.n_threads),
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[](common_params & params, int value) {
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params.cpuparams.n_threads = value;
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if (params.cpuparams.n_threads <= 0) {
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@ -472,14 +446,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"--cpu-strict"}, "<0|1>",
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format("use strict CPU placement (default: %u)\n", (unsigned) params.cpuparams.strict_cpu),
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string_format("use strict CPU placement (default: %u)\n", (unsigned) params.cpuparams.strict_cpu),
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[](common_params & params, const std::string & value) {
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params.cpuparams.strict_cpu = std::stoul(value);
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}
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));
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add_opt(common_arg(
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{"--prio"}, "N",
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format("set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.cpuparams.priority),
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string_format("set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.cpuparams.priority),
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[](common_params & params, int prio) {
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if (prio < 0 || prio > 3) {
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throw std::invalid_argument("invalid value");
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@ -489,7 +463,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"--poll"}, "<0...100>",
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format("use polling level to wait for work (0 - no polling, default: %u)\n", (unsigned) params.cpuparams.poll),
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string_format("use polling level to wait for work (0 - no polling, default: %u)\n", (unsigned) params.cpuparams.poll),
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[](common_params & params, const std::string & value) {
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params.cpuparams.poll = std::stoul(value);
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}
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@ -523,7 +497,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"--prio-batch"}, "N",
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format("set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.cpuparams_batch.priority),
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string_format("set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.cpuparams_batch.priority),
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[](common_params & params, int prio) {
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if (prio < 0 || prio > 3) {
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throw std::invalid_argument("invalid value");
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@ -567,7 +541,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE}));
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add_opt(common_arg(
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{"--prio-draft"}, "N",
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format("set draft process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.draft_cpuparams.priority),
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string_format("set draft process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.draft_cpuparams.priority),
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[](common_params & params, int prio) {
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if (prio < 0 || prio > 3) {
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throw std::invalid_argument("invalid value");
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@ -611,7 +585,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE}));
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add_opt(common_arg(
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{"--prio-batch-draft"}, "N",
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format("set draft process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.draft_cpuparams_batch.priority),
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string_format("set draft process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime (default: %d)\n", params.draft_cpuparams_batch.priority),
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[](common_params & params, int prio) {
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if (prio < 0 || prio > 3) {
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throw std::invalid_argument("invalid value");
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@ -628,14 +602,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE}));
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add_opt(common_arg(
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{"--draft"}, "N",
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format("number of tokens to draft for speculative decoding (default: %d)", params.n_draft),
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string_format("number of tokens to draft for speculative decoding (default: %d)", params.n_draft),
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[](common_params & params, int value) {
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params.n_draft = value;
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}
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP}));
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add_opt(common_arg(
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{"-ps", "--p-split"}, "N",
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format("speculative decoding split probability (default: %.1f)", (double)params.p_split),
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string_format("speculative decoding split probability (default: %.1f)", (double)params.p_split),
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[](common_params & params, const std::string & value) {
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params.p_split = std::stof(value);
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}
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@ -656,56 +630,56 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_LOOKUP}));
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add_opt(common_arg(
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{"-c", "--ctx-size"}, "N",
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format("size of the prompt context (default: %d, 0 = loaded from model)", params.n_ctx),
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string_format("size of the prompt context (default: %d, 0 = loaded from model)", params.n_ctx),
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[](common_params & params, int value) {
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params.n_ctx = value;
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}
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).set_env("LLAMA_ARG_CTX_SIZE"));
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add_opt(common_arg(
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{"-n", "--predict", "--n-predict"}, "N",
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format("number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)", params.n_predict),
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string_format("number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)", params.n_predict),
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[](common_params & params, int value) {
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params.n_predict = value;
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}
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).set_env("LLAMA_ARG_N_PREDICT"));
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add_opt(common_arg(
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{"-b", "--batch-size"}, "N",
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format("logical maximum batch size (default: %d)", params.n_batch),
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string_format("logical maximum batch size (default: %d)", params.n_batch),
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[](common_params & params, int value) {
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params.n_batch = value;
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}
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).set_env("LLAMA_ARG_BATCH"));
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add_opt(common_arg(
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{"-ub", "--ubatch-size"}, "N",
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format("physical maximum batch size (default: %d)", params.n_ubatch),
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string_format("physical maximum batch size (default: %d)", params.n_ubatch),
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[](common_params & params, int value) {
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params.n_ubatch = value;
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}
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).set_env("LLAMA_ARG_UBATCH"));
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add_opt(common_arg(
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{"--keep"}, "N",
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format("number of tokens to keep from the initial prompt (default: %d, -1 = all)", params.n_keep),
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string_format("number of tokens to keep from the initial prompt (default: %d, -1 = all)", params.n_keep),
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[](common_params & params, int value) {
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params.n_keep = value;
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}
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));
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add_opt(common_arg(
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{"--no-context-shift"},
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format("disables context shift on inifinite text generation (default: %s)", params.ctx_shift ? "disabled" : "enabled"),
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string_format("disables context shift on inifinite text generation (default: %s)", params.ctx_shift ? "disabled" : "enabled"),
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[](common_params & params) {
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params.ctx_shift = false;
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}
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).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_NO_CONTEXT_SHIFT"));
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add_opt(common_arg(
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{"--chunks"}, "N",
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format("max number of chunks to process (default: %d, -1 = all)", params.n_chunks),
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string_format("max number of chunks to process (default: %d, -1 = all)", params.n_chunks),
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[](common_params & params, int value) {
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params.n_chunks = value;
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}
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).set_examples({LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_PERPLEXITY, LLAMA_EXAMPLE_RETRIEVAL}));
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add_opt(common_arg(
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{"-fa", "--flash-attn"},
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format("enable Flash Attention (default: %s)", params.flash_attn ? "enabled" : "disabled"),
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string_format("enable Flash Attention (default: %s)", params.flash_attn ? "enabled" : "disabled"),
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[](common_params & params) {
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params.flash_attn = true;
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}
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@ -721,7 +695,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"--no-perf"},
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format("disable internal libllama performance timings (default: %s)", params.no_perf ? "true" : "false"),
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string_format("disable internal libllama performance timings (default: %s)", params.no_perf ? "true" : "false"),
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[](common_params & params) {
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params.no_perf = true;
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params.sparams.no_perf = true;
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@ -733,7 +707,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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std::ifstream file(value);
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if (!file) {
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throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
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throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
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}
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// store the external file name in params
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params.prompt_file = value;
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@ -749,7 +723,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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std::ifstream file(value);
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if (!file) {
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throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
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throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
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}
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params.in_files.push_back(value);
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}
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@ -760,7 +734,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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[](common_params & params, const std::string & value) {
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std::ifstream file(value, std::ios::binary);
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if (!file) {
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throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
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throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
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}
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// store the external file name in params
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params.prompt_file = value;
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@ -772,7 +746,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"-e", "--escape"},
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format("process escapes sequences (\\n, \\r, \\t, \\', \\\", \\\\) (default: %s)", params.escape ? "true" : "false"),
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string_format("process escapes sequences (\\n, \\r, \\t, \\', \\\", \\\\) (default: %s)", params.escape ? "true" : "false"),
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[](common_params & params) {
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params.escape = true;
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}
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@ -786,7 +760,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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));
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add_opt(common_arg(
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{"-ptc", "--print-token-count"}, "N",
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format("print token count every N tokens (default: %d)", params.n_print),
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string_format("print token count every N tokens (default: %d)", params.n_print),
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[](common_params & params, int value) {
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params.n_print = value;
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}
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@ -821,14 +795,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_MAIN}));
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add_opt(common_arg(
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{"-sp", "--special"},
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format("special tokens output enabled (default: %s)", params.special ? "true" : "false"),
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string_format("special tokens output enabled (default: %s)", params.special ? "true" : "false"),
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[](common_params & params) {
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params.special = true;
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}
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).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}));
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add_opt(common_arg(
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{"-cnv", "--conversation"},
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format(
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string_format(
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"run in conversation mode:\n"
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"- does not print special tokens and suffix/prefix\n"
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"- interactive mode is also enabled\n"
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@ -841,14 +815,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_MAIN}));
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add_opt(common_arg(
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{"-i", "--interactive"},
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format("run in interactive mode (default: %s)", params.interactive ? "true" : "false"),
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string_format("run in interactive mode (default: %s)", params.interactive ? "true" : "false"),
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[](common_params & params) {
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params.interactive = true;
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}
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).set_examples({LLAMA_EXAMPLE_MAIN}));
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add_opt(common_arg(
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{"-if", "--interactive-first"},
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format("run in interactive mode and wait for input right away (default: %s)", params.interactive_first ? "true" : "false"),
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string_format("run in interactive mode and wait for input right away (default: %s)", params.interactive_first ? "true" : "false"),
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[](common_params & params) {
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params.interactive_first = true;
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}
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@ -893,7 +867,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_MAIN}));
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add_opt(common_arg(
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{"--spm-infill"},
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format(
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string_format(
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"use Suffix/Prefix/Middle pattern for infill (instead of Prefix/Suffix/Middle) as some models prefer this. (default: %s)",
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params.spm_infill ? "enabled" : "disabled"
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),
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@ -903,7 +877,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_INFILL}));
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add_opt(common_arg(
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{"--samplers"}, "SAMPLERS",
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format("samplers that will be used for generation in the order, separated by \';\'\n(default: %s)", sampler_type_names.c_str()),
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string_format("samplers that will be used for generation in the order, separated by \';\'\n(default: %s)", sampler_type_names.c_str()),
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[](common_params & params, const std::string & value) {
|
||||
const auto sampler_names = string_split(value, ';');
|
||||
params.sparams.samplers = common_sampler_types_from_names(sampler_names, true);
|
||||
|
|
@ -911,14 +885,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"-s", "--seed"}, "SEED",
|
||||
format("RNG seed (default: %d, use random seed for %d)", params.sparams.seed, LLAMA_DEFAULT_SEED),
|
||||
string_format("RNG seed (default: %d, use random seed for %d)", params.sparams.seed, LLAMA_DEFAULT_SEED),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.seed = std::stoul(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--sampling-seq"}, "SEQUENCE",
|
||||
format("simplified sequence for samplers that will be used (default: %s)", sampler_type_chars.c_str()),
|
||||
string_format("simplified sequence for samplers that will be used (default: %s)", sampler_type_chars.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.samplers = common_sampler_types_from_chars(value);
|
||||
}
|
||||
|
|
@ -932,14 +906,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--penalize-nl"},
|
||||
format("penalize newline tokens (default: %s)", params.sparams.penalize_nl ? "true" : "false"),
|
||||
string_format("penalize newline tokens (default: %s)", params.sparams.penalize_nl ? "true" : "false"),
|
||||
[](common_params & params) {
|
||||
params.sparams.penalize_nl = true;
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--temp"}, "N",
|
||||
format("temperature (default: %.1f)", (double)params.sparams.temp),
|
||||
string_format("temperature (default: %.1f)", (double)params.sparams.temp),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.temp = std::stof(value);
|
||||
params.sparams.temp = std::max(params.sparams.temp, 0.0f);
|
||||
|
|
@ -947,42 +921,42 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--top-k"}, "N",
|
||||
format("top-k sampling (default: %d, 0 = disabled)", params.sparams.top_k),
|
||||
string_format("top-k sampling (default: %d, 0 = disabled)", params.sparams.top_k),
|
||||
[](common_params & params, int value) {
|
||||
params.sparams.top_k = value;
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--top-p"}, "N",
|
||||
format("top-p sampling (default: %.1f, 1.0 = disabled)", (double)params.sparams.top_p),
|
||||
string_format("top-p sampling (default: %.1f, 1.0 = disabled)", (double)params.sparams.top_p),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.top_p = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--min-p"}, "N",
|
||||
format("min-p sampling (default: %.1f, 0.0 = disabled)", (double)params.sparams.min_p),
|
||||
string_format("min-p sampling (default: %.1f, 0.0 = disabled)", (double)params.sparams.min_p),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.min_p = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--tfs"}, "N",
|
||||
format("tail free sampling, parameter z (default: %.1f, 1.0 = disabled)", (double)params.sparams.tfs_z),
|
||||
string_format("tail free sampling, parameter z (default: %.1f, 1.0 = disabled)", (double)params.sparams.tfs_z),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.tfs_z = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--typical"}, "N",
|
||||
format("locally typical sampling, parameter p (default: %.1f, 1.0 = disabled)", (double)params.sparams.typ_p),
|
||||
string_format("locally typical sampling, parameter p (default: %.1f, 1.0 = disabled)", (double)params.sparams.typ_p),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.typ_p = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--repeat-last-n"}, "N",
|
||||
format("last n tokens to consider for penalize (default: %d, 0 = disabled, -1 = ctx_size)", params.sparams.penalty_last_n),
|
||||
string_format("last n tokens to consider for penalize (default: %d, 0 = disabled, -1 = ctx_size)", params.sparams.penalty_last_n),
|
||||
[](common_params & params, int value) {
|
||||
params.sparams.penalty_last_n = value;
|
||||
params.sparams.n_prev = std::max(params.sparams.n_prev, params.sparams.penalty_last_n);
|
||||
|
|
@ -990,42 +964,42 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--repeat-penalty"}, "N",
|
||||
format("penalize repeat sequence of tokens (default: %.1f, 1.0 = disabled)", (double)params.sparams.penalty_repeat),
|
||||
string_format("penalize repeat sequence of tokens (default: %.1f, 1.0 = disabled)", (double)params.sparams.penalty_repeat),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.penalty_repeat = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--presence-penalty"}, "N",
|
||||
format("repeat alpha presence penalty (default: %.1f, 0.0 = disabled)", (double)params.sparams.penalty_present),
|
||||
string_format("repeat alpha presence penalty (default: %.1f, 0.0 = disabled)", (double)params.sparams.penalty_present),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.penalty_present = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--frequency-penalty"}, "N",
|
||||
format("repeat alpha frequency penalty (default: %.1f, 0.0 = disabled)", (double)params.sparams.penalty_freq),
|
||||
string_format("repeat alpha frequency penalty (default: %.1f, 0.0 = disabled)", (double)params.sparams.penalty_freq),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.penalty_freq = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--dynatemp-range"}, "N",
|
||||
format("dynamic temperature range (default: %.1f, 0.0 = disabled)", (double)params.sparams.dynatemp_range),
|
||||
string_format("dynamic temperature range (default: %.1f, 0.0 = disabled)", (double)params.sparams.dynatemp_range),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.dynatemp_range = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--dynatemp-exp"}, "N",
|
||||
format("dynamic temperature exponent (default: %.1f)", (double)params.sparams.dynatemp_exponent),
|
||||
string_format("dynamic temperature exponent (default: %.1f)", (double)params.sparams.dynatemp_exponent),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.dynatemp_exponent = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--mirostat"}, "N",
|
||||
format("use Mirostat sampling.\nTop K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.\n"
|
||||
string_format("use Mirostat sampling.\nTop K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.\n"
|
||||
"(default: %d, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)", params.sparams.mirostat),
|
||||
[](common_params & params, int value) {
|
||||
params.sparams.mirostat = value;
|
||||
|
|
@ -1033,14 +1007,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--mirostat-lr"}, "N",
|
||||
format("Mirostat learning rate, parameter eta (default: %.1f)", (double)params.sparams.mirostat_eta),
|
||||
string_format("Mirostat learning rate, parameter eta (default: %.1f)", (double)params.sparams.mirostat_eta),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.mirostat_eta = std::stof(value);
|
||||
}
|
||||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--mirostat-ent"}, "N",
|
||||
format("Mirostat target entropy, parameter tau (default: %.1f)", (double)params.sparams.mirostat_tau),
|
||||
string_format("Mirostat target entropy, parameter tau (default: %.1f)", (double)params.sparams.mirostat_tau),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.mirostat_tau = std::stof(value);
|
||||
}
|
||||
|
|
@ -1069,7 +1043,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_sparam());
|
||||
add_opt(common_arg(
|
||||
{"--grammar"}, "GRAMMAR",
|
||||
format("BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '%s')", params.sparams.grammar.c_str()),
|
||||
string_format("BNF-like grammar to constrain generations (see samples in grammars/ dir) (default: '%s')", params.sparams.grammar.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.sparams.grammar = value;
|
||||
}
|
||||
|
|
@ -1080,7 +1054,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
[](common_params & params, const std::string & value) {
|
||||
std::ifstream file(value);
|
||||
if (!file) {
|
||||
throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
|
||||
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
|
||||
}
|
||||
std::copy(
|
||||
std::istreambuf_iterator<char>(file),
|
||||
|
|
@ -1150,49 +1124,49 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_env("LLAMA_ARG_ROPE_FREQ_SCALE"));
|
||||
add_opt(common_arg(
|
||||
{"--yarn-orig-ctx"}, "N",
|
||||
format("YaRN: original context size of model (default: %d = model training context size)", params.yarn_orig_ctx),
|
||||
string_format("YaRN: original context size of model (default: %d = model training context size)", params.yarn_orig_ctx),
|
||||
[](common_params & params, int value) {
|
||||
params.yarn_orig_ctx = value;
|
||||
}
|
||||
).set_env("LLAMA_ARG_YARN_ORIG_CTX"));
|
||||
add_opt(common_arg(
|
||||
{"--yarn-ext-factor"}, "N",
|
||||
format("YaRN: extrapolation mix factor (default: %.1f, 0.0 = full interpolation)", (double)params.yarn_ext_factor),
|
||||
string_format("YaRN: extrapolation mix factor (default: %.1f, 0.0 = full interpolation)", (double)params.yarn_ext_factor),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.yarn_ext_factor = std::stof(value);
|
||||
}
|
||||
).set_env("LLAMA_ARG_YARN_EXT_FACTOR"));
|
||||
add_opt(common_arg(
|
||||
{"--yarn-attn-factor"}, "N",
|
||||
format("YaRN: scale sqrt(t) or attention magnitude (default: %.1f)", (double)params.yarn_attn_factor),
|
||||
string_format("YaRN: scale sqrt(t) or attention magnitude (default: %.1f)", (double)params.yarn_attn_factor),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.yarn_attn_factor = std::stof(value);
|
||||
}
|
||||
).set_env("LLAMA_ARG_YARN_ATTN_FACTOR"));
|
||||
add_opt(common_arg(
|
||||
{"--yarn-beta-slow"}, "N",
|
||||
format("YaRN: high correction dim or alpha (default: %.1f)", (double)params.yarn_beta_slow),
|
||||
string_format("YaRN: high correction dim or alpha (default: %.1f)", (double)params.yarn_beta_slow),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.yarn_beta_slow = std::stof(value);
|
||||
}
|
||||
).set_env("LLAMA_ARG_YARN_BETA_SLOW"));
|
||||
add_opt(common_arg(
|
||||
{"--yarn-beta-fast"}, "N",
|
||||
format("YaRN: low correction dim or beta (default: %.1f)", (double)params.yarn_beta_fast),
|
||||
string_format("YaRN: low correction dim or beta (default: %.1f)", (double)params.yarn_beta_fast),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.yarn_beta_fast = std::stof(value);
|
||||
}
|
||||
).set_env("LLAMA_ARG_YARN_BETA_FAST"));
|
||||
add_opt(common_arg(
|
||||
{"-gan", "--grp-attn-n"}, "N",
|
||||
format("group-attention factor (default: %d)", params.grp_attn_n),
|
||||
string_format("group-attention factor (default: %d)", params.grp_attn_n),
|
||||
[](common_params & params, int value) {
|
||||
params.grp_attn_n = value;
|
||||
}
|
||||
).set_env("LLAMA_ARG_GRP_ATTN_N"));
|
||||
add_opt(common_arg(
|
||||
{"-gaw", "--grp-attn-w"}, "N",
|
||||
format("group-attention width (default: %.1f)", (double)params.grp_attn_w),
|
||||
string_format("group-attention width (default: %.1f)", (double)params.grp_attn_w),
|
||||
[](common_params & params, int value) {
|
||||
params.grp_attn_w = value;
|
||||
}
|
||||
|
|
@ -1213,7 +1187,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_env("LLAMA_ARG_NO_KV_OFFLOAD"));
|
||||
add_opt(common_arg(
|
||||
{"-ctk", "--cache-type-k"}, "TYPE",
|
||||
format("KV cache data type for K (default: %s)", params.cache_type_k.c_str()),
|
||||
string_format("KV cache data type for K (default: %s)", params.cache_type_k.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
// TODO: get the type right here
|
||||
params.cache_type_k = value;
|
||||
|
|
@ -1221,7 +1195,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_env("LLAMA_ARG_CACHE_TYPE_K"));
|
||||
add_opt(common_arg(
|
||||
{"-ctv", "--cache-type-v"}, "TYPE",
|
||||
format("KV cache data type for V (default: %s)", params.cache_type_v.c_str()),
|
||||
string_format("KV cache data type for V (default: %s)", params.cache_type_v.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
// TODO: get the type right here
|
||||
params.cache_type_v = value;
|
||||
|
|
@ -1229,7 +1203,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_env("LLAMA_ARG_CACHE_TYPE_V"));
|
||||
add_opt(common_arg(
|
||||
{"--perplexity", "--all-logits"},
|
||||
format("return logits for all tokens in the batch (default: %s)", params.logits_all ? "true" : "false"),
|
||||
string_format("return logits for all tokens in the batch (default: %s)", params.logits_all ? "true" : "false"),
|
||||
[](common_params & params) {
|
||||
params.logits_all = true;
|
||||
}
|
||||
|
|
@ -1243,7 +1217,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
|
||||
add_opt(common_arg(
|
||||
{"--hellaswag-tasks"}, "N",
|
||||
format("number of tasks to use when computing the HellaSwag score (default: %zu)", params.hellaswag_tasks),
|
||||
string_format("number of tasks to use when computing the HellaSwag score (default: %zu)", params.hellaswag_tasks),
|
||||
[](common_params & params, int value) {
|
||||
params.hellaswag_tasks = value;
|
||||
}
|
||||
|
|
@ -1257,7 +1231,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
|
||||
add_opt(common_arg(
|
||||
{"--winogrande-tasks"}, "N",
|
||||
format("number of tasks to use when computing the Winogrande score (default: %zu)", params.winogrande_tasks),
|
||||
string_format("number of tasks to use when computing the Winogrande score (default: %zu)", params.winogrande_tasks),
|
||||
[](common_params & params, int value) {
|
||||
params.winogrande_tasks = value;
|
||||
}
|
||||
|
|
@ -1271,7 +1245,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
|
||||
add_opt(common_arg(
|
||||
{"--multiple-choice-tasks"}, "N",
|
||||
format("number of tasks to use when computing the multiple choice score (default: %zu)", params.multiple_choice_tasks),
|
||||
string_format("number of tasks to use when computing the multiple choice score (default: %zu)", params.multiple_choice_tasks),
|
||||
[](common_params & params, int value) {
|
||||
params.multiple_choice_tasks = value;
|
||||
}
|
||||
|
|
@ -1292,42 +1266,42 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
|
||||
add_opt(common_arg(
|
||||
{"--ppl-stride"}, "N",
|
||||
format("stride for perplexity calculation (default: %d)", params.ppl_stride),
|
||||
string_format("stride for perplexity calculation (default: %d)", params.ppl_stride),
|
||||
[](common_params & params, int value) {
|
||||
params.ppl_stride = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
|
||||
add_opt(common_arg(
|
||||
{"--ppl-output-type"}, "<0|1>",
|
||||
format("output type for perplexity calculation (default: %d)", params.ppl_output_type),
|
||||
string_format("output type for perplexity calculation (default: %d)", params.ppl_output_type),
|
||||
[](common_params & params, int value) {
|
||||
params.ppl_output_type = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_PERPLEXITY}));
|
||||
add_opt(common_arg(
|
||||
{"-dt", "--defrag-thold"}, "N",
|
||||
format("KV cache defragmentation threshold (default: %.1f, < 0 - disabled)", (double)params.defrag_thold),
|
||||
string_format("KV cache defragmentation threshold (default: %.1f, < 0 - disabled)", (double)params.defrag_thold),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.defrag_thold = std::stof(value);
|
||||
}
|
||||
).set_env("LLAMA_ARG_DEFRAG_THOLD"));
|
||||
add_opt(common_arg(
|
||||
{"-np", "--parallel"}, "N",
|
||||
format("number of parallel sequences to decode (default: %d)", params.n_parallel),
|
||||
string_format("number of parallel sequences to decode (default: %d)", params.n_parallel),
|
||||
[](common_params & params, int value) {
|
||||
params.n_parallel = value;
|
||||
}
|
||||
).set_env("LLAMA_ARG_N_PARALLEL"));
|
||||
add_opt(common_arg(
|
||||
{"-ns", "--sequences"}, "N",
|
||||
format("number of sequences to decode (default: %d)", params.n_sequences),
|
||||
string_format("number of sequences to decode (default: %d)", params.n_sequences),
|
||||
[](common_params & params, int value) {
|
||||
params.n_sequences = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_PARALLEL}));
|
||||
add_opt(common_arg(
|
||||
{"-cb", "--cont-batching"},
|
||||
format("enable continuous batching (a.k.a dynamic batching) (default: %s)", params.cont_batching ? "enabled" : "disabled"),
|
||||
string_format("enable continuous batching (a.k.a dynamic batching) (default: %s)", params.cont_batching ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.cont_batching = true;
|
||||
}
|
||||
|
|
@ -1451,7 +1425,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
std::vector<std::string> split_arg{ it, {} };
|
||||
if (split_arg.size() >= llama_max_devices()) {
|
||||
throw std::invalid_argument(
|
||||
format("got %d input configs, but system only has %d devices", (int)split_arg.size(), (int)llama_max_devices())
|
||||
string_format("got %d input configs, but system only has %d devices", (int)split_arg.size(), (int)llama_max_devices())
|
||||
);
|
||||
}
|
||||
for (size_t i = 0; i < llama_max_devices(); ++i) {
|
||||
|
|
@ -1468,7 +1442,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_env("LLAMA_ARG_TENSOR_SPLIT"));
|
||||
add_opt(common_arg(
|
||||
{"-mg", "--main-gpu"}, "INDEX",
|
||||
format("the GPU to use for the model (with split-mode = none), or for intermediate results and KV (with split-mode = row) (default: %d)", params.main_gpu),
|
||||
string_format("the GPU to use for the model (with split-mode = none), or for intermediate results and KV (with split-mode = row) (default: %d)", params.main_gpu),
|
||||
[](common_params & params, int value) {
|
||||
params.main_gpu = value;
|
||||
if (!llama_supports_gpu_offload()) {
|
||||
|
|
@ -1478,7 +1452,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_env("LLAMA_ARG_MAIN_GPU"));
|
||||
add_opt(common_arg(
|
||||
{"--check-tensors"},
|
||||
format("check model tensor data for invalid values (default: %s)", params.check_tensors ? "true" : "false"),
|
||||
string_format("check model tensor data for invalid values (default: %s)", params.check_tensors ? "true" : "false"),
|
||||
[](common_params & params) {
|
||||
params.check_tensors = true;
|
||||
}
|
||||
|
|
@ -1489,7 +1463,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
"types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false",
|
||||
[](common_params & params, const std::string & value) {
|
||||
if (!string_parse_kv_override(value.c_str(), params.kv_overrides)) {
|
||||
throw std::runtime_error(format("error: Invalid type for KV override: %s\n", value.c_str()));
|
||||
throw std::runtime_error(string_format("error: Invalid type for KV override: %s\n", value.c_str()));
|
||||
}
|
||||
}
|
||||
));
|
||||
|
|
@ -1543,7 +1517,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
{"-m", "--model"}, "FNAME",
|
||||
ex == LLAMA_EXAMPLE_EXPORT_LORA
|
||||
? std::string("model path from which to load base model")
|
||||
: format(
|
||||
: string_format(
|
||||
"model path (default: `models/$filename` with filename from `--hf-file` "
|
||||
"or `--model-url` if set, otherwise %s)", DEFAULT_MODEL_PATH
|
||||
),
|
||||
|
|
@ -1592,42 +1566,42 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
[](common_params & params, const std::string & value) {
|
||||
std::ifstream file(value, std::ios::binary);
|
||||
if (!file) {
|
||||
throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
|
||||
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
|
||||
}
|
||||
params.context_files.push_back(value);
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_RETRIEVAL}));
|
||||
add_opt(common_arg(
|
||||
{"--chunk-size"}, "N",
|
||||
format("minimum length of embedded text chunks (default: %d)", params.chunk_size),
|
||||
string_format("minimum length of embedded text chunks (default: %d)", params.chunk_size),
|
||||
[](common_params & params, int value) {
|
||||
params.chunk_size = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_RETRIEVAL}));
|
||||
add_opt(common_arg(
|
||||
{"--chunk-separator"}, "STRING",
|
||||
format("separator between chunks (default: '%s')", params.chunk_separator.c_str()),
|
||||
string_format("separator between chunks (default: '%s')", params.chunk_separator.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.chunk_separator = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_RETRIEVAL}));
|
||||
add_opt(common_arg(
|
||||
{"--junk"}, "N",
|
||||
format("number of times to repeat the junk text (default: %d)", params.n_junk),
|
||||
string_format("number of times to repeat the junk text (default: %d)", params.n_junk),
|
||||
[](common_params & params, int value) {
|
||||
params.n_junk = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_PASSKEY}));
|
||||
add_opt(common_arg(
|
||||
{"--pos"}, "N",
|
||||
format("position of the passkey in the junk text (default: %d)", params.i_pos),
|
||||
string_format("position of the passkey in the junk text (default: %d)", params.i_pos),
|
||||
[](common_params & params, int value) {
|
||||
params.i_pos = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_PASSKEY}));
|
||||
add_opt(common_arg(
|
||||
{"-o", "--output", "--output-file"}, "FNAME",
|
||||
format("output file (default: '%s')",
|
||||
string_format("output file (default: '%s')",
|
||||
ex == LLAMA_EXAMPLE_EXPORT_LORA
|
||||
? params.lora_outfile.c_str()
|
||||
: ex == LLAMA_EXAMPLE_CVECTOR_GENERATOR
|
||||
|
|
@ -1641,42 +1615,42 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_IMATRIX, LLAMA_EXAMPLE_CVECTOR_GENERATOR, LLAMA_EXAMPLE_EXPORT_LORA}));
|
||||
add_opt(common_arg(
|
||||
{"-ofreq", "--output-frequency"}, "N",
|
||||
format("output the imatrix every N iterations (default: %d)", params.n_out_freq),
|
||||
string_format("output the imatrix every N iterations (default: %d)", params.n_out_freq),
|
||||
[](common_params & params, int value) {
|
||||
params.n_out_freq = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_IMATRIX}));
|
||||
add_opt(common_arg(
|
||||
{"--save-frequency"}, "N",
|
||||
format("save an imatrix copy every N iterations (default: %d)", params.n_save_freq),
|
||||
string_format("save an imatrix copy every N iterations (default: %d)", params.n_save_freq),
|
||||
[](common_params & params, int value) {
|
||||
params.n_save_freq = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_IMATRIX}));
|
||||
add_opt(common_arg(
|
||||
{"--process-output"},
|
||||
format("collect data for the output tensor (default: %s)", params.process_output ? "true" : "false"),
|
||||
string_format("collect data for the output tensor (default: %s)", params.process_output ? "true" : "false"),
|
||||
[](common_params & params) {
|
||||
params.process_output = true;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_IMATRIX}));
|
||||
add_opt(common_arg(
|
||||
{"--no-ppl"},
|
||||
format("do not compute perplexity (default: %s)", params.compute_ppl ? "true" : "false"),
|
||||
string_format("do not compute perplexity (default: %s)", params.compute_ppl ? "true" : "false"),
|
||||
[](common_params & params) {
|
||||
params.compute_ppl = false;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_IMATRIX}));
|
||||
add_opt(common_arg(
|
||||
{"--chunk", "--from-chunk"}, "N",
|
||||
format("start processing the input from chunk N (default: %d)", params.i_chunk),
|
||||
string_format("start processing the input from chunk N (default: %d)", params.i_chunk),
|
||||
[](common_params & params, int value) {
|
||||
params.i_chunk = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_IMATRIX}));
|
||||
add_opt(common_arg(
|
||||
{"-pps"},
|
||||
format("is the prompt shared across parallel sequences (default: %s)", params.is_pp_shared ? "true" : "false"),
|
||||
string_format("is the prompt shared across parallel sequences (default: %s)", params.is_pp_shared ? "true" : "false"),
|
||||
[](common_params & params) {
|
||||
params.is_pp_shared = true;
|
||||
}
|
||||
|
|
@ -1707,7 +1681,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_BENCH}));
|
||||
add_opt(common_arg(
|
||||
{"--embd-normalize"}, "N",
|
||||
format("normalisation for embendings (default: %d) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)", params.embd_normalize),
|
||||
string_format("normalisation for embendings (default: %d) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)", params.embd_normalize),
|
||||
[](common_params & params, int value) {
|
||||
params.embd_normalize = value;
|
||||
}
|
||||
|
|
@ -1728,35 +1702,35 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_EMBEDDING}));
|
||||
add_opt(common_arg(
|
||||
{"--host"}, "HOST",
|
||||
format("ip address to listen (default: %s)", params.hostname.c_str()),
|
||||
string_format("ip address to listen (default: %s)", params.hostname.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.hostname = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_HOST"));
|
||||
add_opt(common_arg(
|
||||
{"--port"}, "PORT",
|
||||
format("port to listen (default: %d)", params.port),
|
||||
string_format("port to listen (default: %d)", params.port),
|
||||
[](common_params & params, int value) {
|
||||
params.port = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_PORT"));
|
||||
add_opt(common_arg(
|
||||
{"--path"}, "PATH",
|
||||
format("path to serve static files from (default: %s)", params.public_path.c_str()),
|
||||
string_format("path to serve static files from (default: %s)", params.public_path.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.public_path = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_STATIC_PATH"));
|
||||
add_opt(common_arg(
|
||||
{"--embedding", "--embeddings"},
|
||||
format("restrict to only support embedding use case; use only with dedicated embedding models (default: %s)", params.embedding ? "enabled" : "disabled"),
|
||||
string_format("restrict to only support embedding use case; use only with dedicated embedding models (default: %s)", params.embedding ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.embedding = true;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_EMBEDDINGS"));
|
||||
add_opt(common_arg(
|
||||
{"--reranking", "--rerank"},
|
||||
format("enable reranking endpoint on server (default: %s)", params.reranking ? "enabled" : "disabled"),
|
||||
string_format("enable reranking endpoint on server (default: %s)", params.reranking ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.reranking = true;
|
||||
}
|
||||
|
|
@ -1774,7 +1748,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
[](common_params & params, const std::string & value) {
|
||||
std::ifstream key_file(value);
|
||||
if (!key_file) {
|
||||
throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
|
||||
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
|
||||
}
|
||||
std::string key;
|
||||
while (std::getline(key_file, key)) {
|
||||
|
|
@ -1801,7 +1775,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_SSL_CERT_FILE"));
|
||||
add_opt(common_arg(
|
||||
{"-to", "--timeout"}, "N",
|
||||
format("server read/write timeout in seconds (default: %d)", params.timeout_read),
|
||||
string_format("server read/write timeout in seconds (default: %d)", params.timeout_read),
|
||||
[](common_params & params, int value) {
|
||||
params.timeout_read = value;
|
||||
params.timeout_write = value;
|
||||
|
|
@ -1809,7 +1783,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_TIMEOUT"));
|
||||
add_opt(common_arg(
|
||||
{"--threads-http"}, "N",
|
||||
format("number of threads used to process HTTP requests (default: %d)", params.n_threads_http),
|
||||
string_format("number of threads used to process HTTP requests (default: %d)", params.n_threads_http),
|
||||
[](common_params & params, int value) {
|
||||
params.n_threads_http = value;
|
||||
}
|
||||
|
|
@ -1820,7 +1794,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
[](common_params & params, const std::string & value) {
|
||||
std::ifstream file(value);
|
||||
if (!file) {
|
||||
throw std::runtime_error(format("error: failed to open file '%s'\n", value.c_str()));
|
||||
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
|
||||
}
|
||||
std::string system_prompt;
|
||||
std::copy(
|
||||
|
|
@ -1833,21 +1807,21 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_SERVER}));
|
||||
add_opt(common_arg(
|
||||
{"--metrics"},
|
||||
format("enable prometheus compatible metrics endpoint (default: %s)", params.endpoint_metrics ? "enabled" : "disabled"),
|
||||
string_format("enable prometheus compatible metrics endpoint (default: %s)", params.endpoint_metrics ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.endpoint_metrics = true;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ENDPOINT_METRICS"));
|
||||
add_opt(common_arg(
|
||||
{"--slots"},
|
||||
format("enable slots monitoring endpoint (default: %s)", params.endpoint_slots ? "enabled" : "disabled"),
|
||||
string_format("enable slots monitoring endpoint (default: %s)", params.endpoint_slots ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.endpoint_slots = true;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_ENDPOINT_SLOTS"));
|
||||
add_opt(common_arg(
|
||||
{"--props"},
|
||||
format("enable changing global properties via POST /props (default: %s)", params.endpoint_props ? "enabled" : "disabled"),
|
||||
string_format("enable changing global properties via POST /props (default: %s)", params.endpoint_props ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.endpoint_props = true;
|
||||
}
|
||||
|
|
@ -1877,7 +1851,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
"only commonly used templates are accepted:\nhttps://github.com/ggerganov/llama.cpp/wiki/Templates-supported-by-llama_chat_apply_template",
|
||||
[](common_params & params, const std::string & value) {
|
||||
if (!common_chat_verify_template(value)) {
|
||||
throw std::runtime_error(format(
|
||||
throw std::runtime_error(string_format(
|
||||
"error: the supplied chat template is not supported: %s\n"
|
||||
"note: llama.cpp does not use jinja parser, we only support commonly used templates\n",
|
||||
value.c_str()
|
||||
|
|
@ -1888,14 +1862,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CHAT_TEMPLATE"));
|
||||
add_opt(common_arg(
|
||||
{"-sps", "--slot-prompt-similarity"}, "SIMILARITY",
|
||||
format("how much the prompt of a request must match the prompt of a slot in order to use that slot (default: %.2f, 0.0 = disabled)\n", params.slot_prompt_similarity),
|
||||
string_format("how much the prompt of a request must match the prompt of a slot in order to use that slot (default: %.2f, 0.0 = disabled)\n", params.slot_prompt_similarity),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.slot_prompt_similarity = std::stof(value);
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_SERVER}));
|
||||
add_opt(common_arg(
|
||||
{"--lora-init-without-apply"},
|
||||
format("load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: %s)", params.lora_init_without_apply ? "enabled" : "disabled"),
|
||||
string_format("load LoRA adapters without applying them (apply later via POST /lora-adapters) (default: %s)", params.lora_init_without_apply ? "enabled" : "disabled"),
|
||||
[](common_params & params) {
|
||||
params.lora_init_without_apply = true;
|
||||
}
|
||||
|
|
@ -1920,28 +1894,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
|
|||
));
|
||||
add_opt(common_arg(
|
||||
{"--positive-file"}, "FNAME",
|
||||
format("positive prompts file, one prompt per line (default: '%s')", params.cvector_positive_file.c_str()),
|
||||
string_format("positive prompts file, one prompt per line (default: '%s')", params.cvector_positive_file.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.cvector_positive_file = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_CVECTOR_GENERATOR}));
|
||||
add_opt(common_arg(
|
||||
{"--negative-file"}, "FNAME",
|
||||
format("negative prompts file, one prompt per line (default: '%s')", params.cvector_negative_file.c_str()),
|
||||
string_format("negative prompts file, one prompt per line (default: '%s')", params.cvector_negative_file.c_str()),
|
||||
[](common_params & params, const std::string & value) {
|
||||
params.cvector_negative_file = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_CVECTOR_GENERATOR}));
|
||||
add_opt(common_arg(
|
||||
{"--pca-batch"}, "N",
|
||||
format("batch size used for PCA. Larger batch runs faster, but uses more memory (default: %d)", params.n_pca_batch),
|
||||
string_format("batch size used for PCA. Larger batch runs faster, but uses more memory (default: %d)", params.n_pca_batch),
|
||||
[](common_params & params, int value) {
|
||||
params.n_pca_batch = value;
|
||||
}
|
||||
).set_examples({LLAMA_EXAMPLE_CVECTOR_GENERATOR}));
|
||||
add_opt(common_arg(
|
||||
{"--pca-iter"}, "N",
|
||||
format("number of iterations used for PCA (default: %d)", params.n_pca_iterations),
|
||||
string_format("number of iterations used for PCA (default: %d)", params.n_pca_iterations),
|
||||
[](common_params & params, int value) {
|
||||
params.n_pca_iterations = value;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@
|
|||
|
||||
#include <algorithm>
|
||||
#include <cinttypes>
|
||||
#include <climits>
|
||||
#include <cmath>
|
||||
#include <codecvt>
|
||||
#include <cstdarg>
|
||||
|
|
@ -23,10 +24,10 @@
|
|||
#include <regex>
|
||||
#include <sstream>
|
||||
#include <string>
|
||||
#include <thread>
|
||||
#include <unordered_map>
|
||||
#include <unordered_set>
|
||||
#include <vector>
|
||||
#include <thread>
|
||||
|
||||
#if defined(__APPLE__) && defined(__MACH__)
|
||||
#include <sys/types.h>
|
||||
|
|
@ -400,6 +401,21 @@ std::string common_params_get_system_info(const common_params & params) {
|
|||
// String utils
|
||||
//
|
||||
|
||||
std::string string_format(const char * fmt, ...) {
|
||||
va_list ap;
|
||||
va_list ap2;
|
||||
va_start(ap, fmt);
|
||||
va_copy(ap2, ap);
|
||||
int size = vsnprintf(NULL, 0, fmt, ap);
|
||||
GGML_ASSERT(size >= 0 && size < INT_MAX); // NOLINT
|
||||
std::vector<char> buf(size + 1);
|
||||
int size2 = vsnprintf(buf.data(), size + 1, fmt, ap2);
|
||||
GGML_ASSERT(size2 == size);
|
||||
va_end(ap2);
|
||||
va_end(ap);
|
||||
return std::string(buf.data(), size);
|
||||
}
|
||||
|
||||
std::vector<std::string> string_split(std::string input, char separator) {
|
||||
std::vector<std::string> parts;
|
||||
size_t separator_pos = input.find(separator);
|
||||
|
|
|
|||
|
|
@ -352,15 +352,28 @@ void common_init();
|
|||
|
||||
std::string common_params_get_system_info(const common_params & params);
|
||||
|
||||
bool parse_cpu_range(const std::string& range, bool(&boolmask)[GGML_MAX_N_THREADS]);
|
||||
bool parse_cpu_mask(const std::string& mask, bool(&boolmask)[GGML_MAX_N_THREADS]);
|
||||
void postprocess_cpu_params(cpu_params& cpuparams, const cpu_params* role_model = nullptr);
|
||||
bool parse_cpu_range(const std::string & range, bool(&boolmask)[GGML_MAX_N_THREADS]);
|
||||
bool parse_cpu_mask(const std::string & mask, bool(&boolmask)[GGML_MAX_N_THREADS]);
|
||||
void postprocess_cpu_params(cpu_params & cpuparams, const cpu_params * role_model = nullptr);
|
||||
bool set_process_priority(enum ggml_sched_priority prio);
|
||||
|
||||
//
|
||||
// String utils
|
||||
//
|
||||
|
||||
#ifdef __GNUC__
|
||||
#ifdef __MINGW32__
|
||||
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(gnu_printf, __VA_ARGS__)))
|
||||
#else
|
||||
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...) __attribute__((format(printf, __VA_ARGS__)))
|
||||
#endif
|
||||
#else
|
||||
#define LLAMA_COMMON_ATTRIBUTE_FORMAT(...)
|
||||
#endif
|
||||
|
||||
LLAMA_COMMON_ATTRIBUTE_FORMAT(1, 2)
|
||||
std::string string_format(const char * fmt, ...);
|
||||
|
||||
std::vector<std::string> string_split(std::string input, char separator);
|
||||
|
||||
std::string string_strip(const std::string & str);
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue