common : use two decimal places for float arg help messages (#19048)
* common : use two decimal places for float arg help messages This commit updates the help messages for various command-line arguments in arg.cpp to display floating-point default values with two decimal places instead of one. The motivation for this changes is that currently only having one decimal place means that values generated using --help or llama-gen-docs will not display the correct values. For example, currently the value of top-p in tools/server/README.md is `0.9`, but the default value is actually '0.95'. And running llama-gen-docs does not update this value as it uses the output from the help message, which shows only one decimal place, so the values look like they are unchanged. * docs : run llama-gen-docs to update docs
This commit is contained in:
Daniel Bevenius
GitHub
parent
9981c30130
commit
16639ba217
4 changed files with 94 additions and 91 deletions
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@ -1577,7 +1577,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--temp"}, "N",
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string_format("temperature (default: %.1f)", (double)params.sampling.temp),
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string_format("temperature (default: %.2f)", (double)params.sampling.temp),
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[](common_params & params, const std::string & value) {
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params.sampling.temp = std::stof(value);
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params.sampling.temp = std::max(params.sampling.temp, 0.0f);
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@ -1594,7 +1594,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam().set_env("LLAMA_ARG_TOP_K"));
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add_opt(common_arg(
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{"--top-p"}, "N",
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string_format("top-p sampling (default: %.1f, 1.0 = disabled)", (double)params.sampling.top_p),
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string_format("top-p sampling (default: %.2f, 1.0 = disabled)", (double)params.sampling.top_p),
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[](common_params & params, const std::string & value) {
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params.sampling.top_p = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_TOP_P;
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@ -1602,7 +1602,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--min-p"}, "N",
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string_format("min-p sampling (default: %.1f, 0.0 = disabled)", (double)params.sampling.min_p),
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string_format("min-p sampling (default: %.2f, 0.0 = disabled)", (double)params.sampling.min_p),
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[](common_params & params, const std::string & value) {
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params.sampling.min_p = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIN_P;
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@ -1610,14 +1610,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--top-nsigma"}, "N",
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string_format("top-n-sigma sampling (default: %.1f, -1.0 = disabled)", params.sampling.top_n_sigma),
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string_format("top-n-sigma sampling (default: %.2f, -1.0 = disabled)", params.sampling.top_n_sigma),
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[](common_params & params, const std::string & value) {
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params.sampling.top_n_sigma = std::stof(value);
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}
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).set_sparam());
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add_opt(common_arg(
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{"--xtc-probability"}, "N",
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string_format("xtc probability (default: %.1f, 0.0 = disabled)", (double)params.sampling.xtc_probability),
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string_format("xtc probability (default: %.2f, 0.0 = disabled)", (double)params.sampling.xtc_probability),
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[](common_params & params, const std::string & value) {
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params.sampling.xtc_probability = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_XTC_PROBABILITY;
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@ -1625,7 +1625,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--xtc-threshold"}, "N",
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string_format("xtc threshold (default: %.1f, 1.0 = disabled)", (double)params.sampling.xtc_threshold),
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string_format("xtc threshold (default: %.2f, 1.0 = disabled)", (double)params.sampling.xtc_threshold),
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[](common_params & params, const std::string & value) {
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params.sampling.xtc_threshold = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_XTC_THRESHOLD;
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@ -1633,7 +1633,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--typical"}, "N",
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string_format("locally typical sampling, parameter p (default: %.1f, 1.0 = disabled)", (double)params.sampling.typ_p),
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string_format("locally typical sampling, parameter p (default: %.2f, 1.0 = disabled)", (double)params.sampling.typ_p),
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[](common_params & params, const std::string & value) {
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params.sampling.typ_p = std::stof(value);
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}
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@ -1652,7 +1652,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--repeat-penalty"}, "N",
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string_format("penalize repeat sequence of tokens (default: %.1f, 1.0 = disabled)", (double)params.sampling.penalty_repeat),
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string_format("penalize repeat sequence of tokens (default: %.2f, 1.0 = disabled)", (double)params.sampling.penalty_repeat),
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[](common_params & params, const std::string & value) {
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params.sampling.penalty_repeat = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_PENALTY_REPEAT;
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@ -1660,21 +1660,21 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--presence-penalty"}, "N",
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string_format("repeat alpha presence penalty (default: %.1f, 0.0 = disabled)", (double)params.sampling.penalty_present),
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string_format("repeat alpha presence penalty (default: %.2f, 0.0 = disabled)", (double)params.sampling.penalty_present),
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[](common_params & params, const std::string & value) {
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params.sampling.penalty_present = std::stof(value);
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}
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).set_sparam());
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add_opt(common_arg(
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{"--frequency-penalty"}, "N",
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string_format("repeat alpha frequency penalty (default: %.1f, 0.0 = disabled)", (double)params.sampling.penalty_freq),
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string_format("repeat alpha frequency penalty (default: %.2f, 0.0 = disabled)", (double)params.sampling.penalty_freq),
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[](common_params & params, const std::string & value) {
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params.sampling.penalty_freq = std::stof(value);
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}
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).set_sparam());
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add_opt(common_arg(
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{"--dry-multiplier"}, "N",
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string_format("set DRY sampling multiplier (default: %.1f, 0.0 = disabled)", (double)params.sampling.dry_multiplier),
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string_format("set DRY sampling multiplier (default: %.2f, 0.0 = disabled)", (double)params.sampling.dry_multiplier),
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[](common_params & params, const std::string & value) {
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params.sampling.dry_multiplier = std::stof(value);
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}
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@ -1755,14 +1755,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--dynatemp-range"}, "N",
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string_format("dynamic temperature range (default: %.1f, 0.0 = disabled)", (double)params.sampling.dynatemp_range),
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string_format("dynamic temperature range (default: %.2f, 0.0 = disabled)", (double)params.sampling.dynatemp_range),
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[](common_params & params, const std::string & value) {
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params.sampling.dynatemp_range = std::stof(value);
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}
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).set_sparam());
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add_opt(common_arg(
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{"--dynatemp-exp"}, "N",
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string_format("dynamic temperature exponent (default: %.1f)", (double)params.sampling.dynatemp_exponent),
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string_format("dynamic temperature exponent (default: %.2f)", (double)params.sampling.dynatemp_exponent),
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[](common_params & params, const std::string & value) {
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params.sampling.dynatemp_exponent = std::stof(value);
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}
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@ -1778,7 +1778,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--mirostat-lr"}, "N",
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string_format("Mirostat learning rate, parameter eta (default: %.1f)", (double)params.sampling.mirostat_eta),
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string_format("Mirostat learning rate, parameter eta (default: %.2f)", (double)params.sampling.mirostat_eta),
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[](common_params & params, const std::string & value) {
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params.sampling.mirostat_eta = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIROSTAT_ETA;
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@ -1786,7 +1786,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_sparam());
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add_opt(common_arg(
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{"--mirostat-ent"}, "N",
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string_format("Mirostat target entropy, parameter tau (default: %.1f)", (double)params.sampling.mirostat_tau),
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string_format("Mirostat target entropy, parameter tau (default: %.2f)", (double)params.sampling.mirostat_tau),
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[](common_params & params, const std::string & value) {
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params.sampling.mirostat_tau = std::stof(value);
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params.sampling.user_sampling_config |= common_params_sampling_config::COMMON_PARAMS_SAMPLING_CONFIG_MIROSTAT_TAU;
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@ -1920,28 +1920,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_env("LLAMA_ARG_YARN_ORIG_CTX"));
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add_opt(common_arg(
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{"--yarn-ext-factor"}, "N",
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string_format("YaRN: extrapolation mix factor (default: %.1f, 0.0 = full interpolation)", (double)params.yarn_ext_factor),
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string_format("YaRN: extrapolation mix factor (default: %.2f, 0.0 = full interpolation)", (double)params.yarn_ext_factor),
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[](common_params & params, const std::string & value) {
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params.yarn_ext_factor = std::stof(value);
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}
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).set_env("LLAMA_ARG_YARN_EXT_FACTOR"));
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add_opt(common_arg(
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{"--yarn-attn-factor"}, "N",
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string_format("YaRN: scale sqrt(t) or attention magnitude (default: %.1f)", (double)params.yarn_attn_factor),
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string_format("YaRN: scale sqrt(t) or attention magnitude (default: %.2f)", (double)params.yarn_attn_factor),
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[](common_params & params, const std::string & value) {
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params.yarn_attn_factor = std::stof(value);
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}
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).set_env("LLAMA_ARG_YARN_ATTN_FACTOR"));
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add_opt(common_arg(
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{"--yarn-beta-slow"}, "N",
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string_format("YaRN: high correction dim or alpha (default: %.1f)", (double)params.yarn_beta_slow),
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string_format("YaRN: high correction dim or alpha (default: %.2f)", (double)params.yarn_beta_slow),
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[](common_params & params, const std::string & value) {
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params.yarn_beta_slow = std::stof(value);
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}
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).set_env("LLAMA_ARG_YARN_BETA_SLOW"));
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add_opt(common_arg(
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{"--yarn-beta-fast"}, "N",
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string_format("YaRN: low correction dim or beta (default: %.1f)", (double)params.yarn_beta_fast),
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string_format("YaRN: low correction dim or beta (default: %.2f)", (double)params.yarn_beta_fast),
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[](common_params & params, const std::string & value) {
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params.yarn_beta_fast = std::stof(value);
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}
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@ -3335,14 +3335,14 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_LOOKUP, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_DRAFT_MIN"));
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add_opt(common_arg(
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{"--draft-p-split"}, "P",
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string_format("speculative decoding split probability (default: %.1f)", (double)params.speculative.p_split),
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string_format("speculative decoding split probability (default: %.2f)", (double)params.speculative.p_split),
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[](common_params & params, const std::string & value) {
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params.speculative.p_split = std::stof(value);
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}
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).set_examples({LLAMA_EXAMPLE_SPECULATIVE}).set_env("LLAMA_ARG_DRAFT_P_SPLIT"));
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add_opt(common_arg(
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{"--draft-p-min"}, "P",
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string_format("minimum speculative decoding probability (greedy) (default: %.1f)", (double)params.speculative.p_min),
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string_format("minimum speculative decoding probability (greedy) (default: %.2f)", (double)params.speculative.p_min),
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[](common_params & params, const std::string & value) {
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params.speculative.p_min = std::stof(value);
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}
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