mirror of
https://github.com/ikawrakow/ik_llama.cpp.git
synced 2026-08-12 22:29:39 +04:00
Chores: tidy up common.cpp + 5 new aliases (#2220)
* Short aliases for context checkpoints * common: fix typos and add/document obvious short aliases Typos fixed in --help output: - Swapped long names for -ctv-last/-ctk-last: --cache-type-k-last and --cache-type-v-last now match their K/V semantics - --scheduler-async (was --scheduler_async) and fix stray ')' in its help text - Remove stray trailing commas in --merge-qkv, --merge-up-gate-experts, --k-cache-hadamard, --v-cache-hadamard, --split-mode-f16, --split-mode-f32, --split-mode-graph-scheduling - 'top-n-sigma parmeter' -> 'parameter' - 'embendings' -> 'embeddings' (2x) Short aliases: - New: -okv alias for --override-kv - Document previously undocumented aliases in --help: -rtr, -cmoe, -ncmoe, -thp (also adds the previously missing --transparent-huge-pages entry), -ofreq, -to, -spf * common: standardize arg parser to short-alias-first ordering gpt_params_find_arg now consistently lists the short alias before the full --long-name argument, matching the dominant convention (103 short-first lines). Reordered 19 options that had the long name first: -gan, -gaw, -dt, -mea, -ps, -mtprot, -mg, -sm, -ts, -ot, -gfm, -cmoe, -ncmoe, -dr, -op, -no-ooae, -to, -sps, -wb. Pure style change, no functional impact. * common: systematize cache-type help order, fix -cram-n-min help - Reorder the mixed KV cache-type help entries to k-first, k-last, v-first, v-last for logical grouping (short alias, then full name, matching the parser convention) - -cram-n-min now shows its N argument in --help (was missing)
This commit is contained in:
Nexesenex
+53
-52
@@ -1246,12 +1246,12 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.speculative.n_ctx = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--grp-attn-n" || arg == "-gan") {
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if (arg == "-gan" || arg == "--grp-attn-n") {
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CHECK_ARG
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params.grp_attn_n = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--grp-attn-w" || arg == "-gaw") {
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if (arg == "-gaw" || arg == "--grp-attn-w") {
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CHECK_ARG
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params.grp_attn_w = std::stoi(argv[i]);
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return true;
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@@ -1323,12 +1323,12 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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else { invalid_param = true; }
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return true;
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}
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if (arg == "--defrag-thold" || arg == "-dt") {
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if (arg == "-dt" || arg == "--defrag-thold") {
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CHECK_ARG
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params.defrag_thold = std::stof(argv[i]);
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return true;
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}
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if (arg == "--max-extra-alloc" || arg == "-mea") {
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if (arg == "-mea" || arg == "--max-extra-alloc") {
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CHECK_ARG
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params.max_extra_alloc_MiB = std::stoi(argv[i]);
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return true;
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@@ -1592,7 +1592,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.n_sequences = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--p-split" || arg == "-ps") {
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if (arg == "-ps" || arg == "--p-split") {
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CHECK_ARG
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params.p_split = std::stof(argv[i]);
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return true;
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@@ -1856,7 +1856,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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}
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return true;
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}
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if (arg == "--mtp-requantize-output-tensor" || arg == "-mtprot") {
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if (arg == "-mtprot" || arg == "--mtp-requantize-output-tensor") {
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CHECK_ARG
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params.extra_output_type = argv[i];
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return true;
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@@ -2000,7 +2000,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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}
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return true;
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}
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if (arg == "--main-gpu" || arg == "-mg") {
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if (arg == "-mg" || arg == "--main-gpu") {
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CHECK_ARG
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params.main_gpu = std::stoi(argv[i]);
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#ifndef GGML_USE_CUDA_SYCL_VULKAN
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@@ -2013,7 +2013,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.max_gpu = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--split-mode" || arg == "-sm") {
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if (arg == "-sm" || arg == "--split-mode") {
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CHECK_ARG
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std::string arg_next = argv[i];
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if (arg_next == "none") {
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@@ -2037,7 +2037,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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#endif // GGML_USE_CUDA_SYCL_VULKAN
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return true;
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}
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if (arg == "--tensor-split" || arg == "-ts") {
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if (arg == "-ts" || arg == "--tensor-split") {
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CHECK_ARG
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std::string arg_next = argv[i];
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@@ -2074,7 +2074,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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#endif
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return true;
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}
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if (arg == "--override-kv") {
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if (arg == "-okv" || arg == "--override-kv") {
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CHECK_ARG
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if (!string_parse_kv_override(argv[i], params.kv_overrides)) {
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fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]);
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@@ -2083,7 +2083,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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}
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return true;
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}
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if (arg == "--override-tensor" || arg == "-ot") {
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if (arg == "-ot" || arg == "--override-tensor") {
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CHECK_ARG
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if (!parse_buft_overrides(std::string{ argv[i] }, params.tensor_buft_overrides)) {
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fprintf(stderr, "error: Invalid tensor buffer type override: %s\n", argv[i]);
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@@ -2091,7 +2091,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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}
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return true;
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}
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if (arg == "--gpu-fit-margin" || arg == "-gfm") {
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if (arg == "-gfm" || arg == "--gpu-fit-margin") {
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CHECK_ARG
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auto p = string_split_pairs<int,int>(argv[i], ',');
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if (p.empty()) {
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@@ -2126,12 +2126,12 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.speculative.params = argv[i];
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return true;
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}
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if (arg == "--cpu-moe" || arg == "-cmoe") {
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if (arg == "-cmoe" || arg == "--cpu-moe") {
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params.ncmoe = 999;
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//params.tensor_buft_overrides.push_back({strdup("\\.ffn_(up|down|gate|gate_up)_exps\\.weight"), ggml_backend_cpu_buffer_type()});
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return true;
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}
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if (arg == "--n-cpu-moe" || arg == "-ncmoe") {
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if (arg == "-ncmoe" || arg == "--n-cpu-moe") {
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CHECK_ARG
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int32_t n_layers = std::stoi(argv[i]);
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if (n_layers < 0) {
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@@ -2453,7 +2453,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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fprintf(stderr, "built with %s for %s\n", LLAMA_COMPILER, LLAMA_BUILD_TARGET);
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exit(0);
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}
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if (arg == "--dry-run" || arg == "-dr") {
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if (arg == "-dr" || arg == "--dry-run") {
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params.dry_run = true;
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return true;
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}
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@@ -2500,7 +2500,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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return true;
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}
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if (arg == "--offload-policy" || arg == "-op") {
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if (arg == "-op" || arg == "--offload-policy") {
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CHECK_ARG
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auto p = string_split_pairs<int,int>(argv[i], ',');
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if (p.empty()) {
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@@ -2511,7 +2511,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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}
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return true;
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}
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if (arg == "--no-offload-only-active-experts" || arg == "-no-ooae") {
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if (arg == "-no-ooae" || arg == "--no-offload-only-active-experts") {
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params.only_active_exps = false;
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return true;
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}
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@@ -2575,7 +2575,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.ssl_file_cert = argv[i];
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return true;
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}
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if (arg == "--timeout" || arg == "-to") {
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if (arg == "-to" || arg == "--timeout") {
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CHECK_ARG
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params.timeout_read = std::stoi(argv[i]);
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params.timeout_write = std::stoi(argv[i]);
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@@ -2735,7 +2735,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.parallel_tool_calls = true;
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return true;
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}
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if (arg == "--slot-prompt-similarity" || arg == "-sps") {
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if (arg == "-sps" || arg == "--slot-prompt-similarity") {
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CHECK_ARG
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params.slot_prompt_similarity = std::stof(argv[i]);
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return true;
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@@ -2807,22 +2807,22 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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}
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return true;
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}
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if (arg == "--ctx-checkpoints") {
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if (arg == "-ctx-ckpt" || arg == "--ctx-checkpoints") {
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CHECK_ARG
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params.ctx_checkpoints_n = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--ctx-checkpoints-interval") {
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if (arg == "-ctx-ckpt-i" || arg == "--ctx-checkpoints-interval") {
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CHECK_ARG
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params.ctx_checkpoints_interval = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--ctx-checkpoints-tolerance") {
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if (arg == "-ctx-ckpt-t" || arg == "--ctx-checkpoints-tolerance") {
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CHECK_ARG
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params.ctx_checkpoints_tolerance = std::stoi(argv[i]);
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return true;
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}
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if (arg == "--ctx-checkpoints-eviction") {
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if (arg == "-ctx-ckpt-e" || arg == "--ctx-checkpoints-eviction") {
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CHECK_ARG
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params.ctx_checkpoint_eviction= common_checkpoint_eviction_from_name(std::string(argv[i]));
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return true;
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@@ -2923,7 +2923,7 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa
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params.warmup = false;
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return true;
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}
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if (arg == "--warmup-batch" || arg == "-wb") {
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if (arg == "-wb" || arg == "--warmup-batch") {
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params.batch_warmup = true;
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return true;
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}
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@@ -3035,13 +3035,13 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
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options.push_back({ "*", "-c, --ctx-size N", "size of the prompt context (default: %d, 0 = loaded from model)", params.n_ctx });
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options.push_back({ "*", "-cd, --ctx-size-draft N", "size of the prompt context for the draft model (default: %d, 0 = loaded from model)", params.speculative.n_ctx });
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options.push_back({ "*", "--ctx-checkpoints N", "max number of context checkpoints to create per slot (default: %d)",params.ctx_checkpoints_n});
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options.push_back({ "*", "--ctx-checkpoints-interval N", "minimum number of tokens between each context checkpoint. (default: %d, <=0 disable)",params.ctx_checkpoints_interval});
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options.push_back({ "*", "--ctx-checkpoints-tolerance N", "the number of tokens before the full prompt to create the checkpoint. (default: %d, <=0 disable)",params.ctx_checkpoints_tolerance});
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options.push_back({ "*", "--ctx-checkpoints-eviction NAME", "Eviction strategy for checkpoint. Accepts fifo, variance and auto. Auto defaults to variance. Variance preserves coverage and maintains uniform interval. (default: variance)" });
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options.push_back({ "*", "-ctx-ckpt N, --ctx-checkpoints N", "max number of context checkpoints to create per slot (default: %d)",params.ctx_checkpoints_n});
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options.push_back({ "*", "-ctx-ckpt-i N, --ctx-checkpoints-interval N", "minimum number of tokens between each context checkpoint. (default: %d, <=0 disable)",params.ctx_checkpoints_interval});
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options.push_back({ "*", "-ctx-ckpt-t N, --ctx-checkpoints-tolerance N", "the number of tokens before the full prompt to create the checkpoint. (default: %d, <=0 disable)",params.ctx_checkpoints_tolerance});
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options.push_back({ "*", "-ctx-ckpt-e NAME, --ctx-checkpoints-eviction NAME", "Eviction strategy for checkpoint. Accepts fifo, variance and auto. Auto defaults to variance. Variance preserves coverage and maintains uniform interval. (default: variance)" });
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options.push_back({ "*", "-cram, --cache-ram N", "set the maximum cache size in MiB (default: %d, -1 - no limit, 0 - disable)",params.cache_ram_mib });
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options.push_back({ "*", "-crs, --cache-ram-similarity N", "max of similarity of prompt tokens to cache tokens that triggers prompt cache (default: %.2f).",params.cache_ram_similarity });
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options.push_back({ "*", "-cram-n-min --cache-ram-n-min N", "minimum number of the cached tokens that triggers prompt cache (default: %d).", params.cache_ram_n_min });
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options.push_back({ "*", "-cram-n-min N, --cache-ram-n-min N", "minimum number of the cached tokens that triggers prompt cache (default: %d).", params.cache_ram_n_min });
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options.push_back({ "*", "-n, --predict N", "number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)", params.n_predict });
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options.push_back({ "*", "-b, --batch-size N", "logical maximum batch size (default: %d)", params.n_batch });
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options.push_back({ "*", "-ub, --ubatch-size N", "physical maximum batch size (default: %d)", params.n_ubatch });
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@@ -3062,16 +3062,16 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
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options.push_back({ "*", "-gr, --graph-reuse", "enable graph reuse (default: %s)", params.graph_reuse ? "enabled" : "disabled" });
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options.push_back({ "*", "-no-gr, --no-graph-reuse", "disable graph reuse (default: %s)", !params.graph_reuse ? "enabled" : "disabled" });
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options.push_back({ "*", "-ser, --smart-expert-reduction", "experts reduction (default: %d,%g)", params.min_experts, params.thresh_experts});
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options.push_back({ "*", "-mqkv, --merge-qkv,", "merge Q,K,V (default: %d)", params.merge_qkv});
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options.push_back({ "*", "-muge, --merge-up-gate-experts,","merge ffn_up/gate_exps (default: %d)", params.merge_up_gate_exps});
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options.push_back({ "*", "-khad, --k-cache-hadamard,", "Use Hadamard transform for K-cache (default: %d)", params.k_cache_hadamard});
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options.push_back({ "*", "-vhad, --v-cache-hadamard,", "Use Hadamard transform for V-cache (default: %d)", params.v_cache_hadamard});
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options.push_back({ "*", "-smf16, --split-mode-f16,", "Use f16 for data exchange between GPUs (default: %d)", true});
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options.push_back({ "*", "-smf32, --split-mode-f32,", "Use f32 for data exchange between GPUs (default: %d)", false});
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options.push_back({ "*", "-mqkv, --merge-qkv", "merge Q,K,V (default: %d)", params.merge_qkv});
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options.push_back({ "*", "-muge, --merge-up-gate-experts","merge ffn_up/gate_exps (default: %d)", params.merge_up_gate_exps});
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options.push_back({ "*", "-khad, --k-cache-hadamard", "Use Hadamard transform for K-cache (default: %d)", params.k_cache_hadamard});
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options.push_back({ "*", "-vhad, --v-cache-hadamard", "Use Hadamard transform for V-cache (default: %d)", params.v_cache_hadamard});
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options.push_back({ "*", "-smf16, --split-mode-f16", "Use f16 for data exchange between GPUs (default: %d)", true});
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options.push_back({ "*", "-smf32, --split-mode-f32", "Use f32 for data exchange between GPUs (default: %d)", false});
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options.push_back({ "*", "-grt, --graph-reduce-type", "Type for data exchange between GPUs (default: %s)", "f32"});
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options.push_back({ "*", "-gap, --graph-attn-precision", "Flash-attn precision under -sm graph (default: %s)", "f16"});
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options.push_back({ "*", "-smgs, --split-mode-graph-scheduling,", "Force Split Mode Graph Scheduling (default: %d)", params.split_mode_graph_scheduling});
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options.push_back({ "*", "-sas, --scheduler_async,", "Async evaluation of compute graphs: %d)", params.scheduler_async});
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options.push_back({ "*", "-smgs, --split-mode-graph-scheduling", "Force Split Mode Graph Scheduling (default: %d)", params.split_mode_graph_scheduling});
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options.push_back({ "*", "-sas, --scheduler-async", "Async evaluation of compute graphs (default: %d)", params.scheduler_async});
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options.push_back({ "*", "-vq, --validate-quants", "validate quantized data while loading the model (default: %d)", params.validate_quants});
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options.push_back({ "*", "-p, --prompt PROMPT", "prompt to start generation with\n"
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"in conversation mode, this will be used as system prompt\n"
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@@ -3135,7 +3135,7 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
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options.push_back({ "*", " --dry-allowed-length N", "DRY sampling allowed length (default: %d)", sparams.dry_allowed_length });
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options.push_back({ "*", " --dry-penalty-last-n N", "DRY sampling penalty last N tokens (default: %d, 0 = disabled, -1 = context size)", sparams.dry_penalty_last_n });
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options.push_back({ "*", " --dry-sequence-breaker STR", "DRY sampling sequence breaker characters (each char becomes a breaker) or 'none' to clear" });
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options.push_back({ "*", " --top-n-sigma t", "top-n-sigma parmeter (default: %.1f, 0.0 = disabled)", (double)sparams.top_n_sigma});
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options.push_back({ "*", " --top-n-sigma t", "top-n-sigma parameter (default: %.1f, 0.0 = disabled)", (double)sparams.top_n_sigma});
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options.push_back({ "*", " --adaptive-target", "adaptive-p sampling: (default: %.2f, <0.0 = disabled)", (double)sparams.adaptive_target});
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options.push_back({ "*", " --adaptive-decay", "adaptive-p sampling: (default: %.2f)", (double)sparams.adaptive_decay});
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options.push_back({ "*", " --adaptive-updt-w-cur", "adaptive-p sampling: (default: %s)", sparams.adaptive_updt_w_cur ? "true" : "false"});
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@@ -3224,9 +3224,9 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
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options.push_back({ "*", "-ictk, --indexer-cache-type-k TYPE", "indexer K-cache data type (default: %s)", params.indexer_cache_type_k.c_str() });
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options.push_back({ "*", "-ctv, --cache-type-v TYPE", "KV cache data type for V (default: %s)", params.cache_type_v.c_str() });
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options.push_back({ "*", "-ctk-first, --cache-type-k-first TYPE,N", "KV cache data type for the first N layers of K (default: %s,-1)", params.type_k_first.c_str() });
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options.push_back({ "*", "-ctv-last, --cache-type-k-last TYPE,N", "KV cache data type for the last N layers of K (default: %s,-1)", params.type_k_last.c_str() });
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options.push_back({ "*", "-ctk-last, --cache-type-k-last TYPE,N", "KV cache data type for the last N layers of K (default: %s,-1)", params.type_k_last.c_str() });
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options.push_back({ "*", "-ctv-first, --cache-type-v-first TYPE,N", "KV cache data type for the first N layers of V (default: %s,-1)", params.type_v_first.c_str() });
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options.push_back({ "*", "-ctk-last, --cache-type-v-last TYPE,N", "KV cache data type for the last N layers of V (default: %s,-1)", params.type_v_last.c_str() });
|
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options.push_back({ "*", "-ctv-last, --cache-type-v-last TYPE,N", "KV cache data type for the last N layers of V (default: %s,-1)", params.type_v_last.c_str() });
|
||||
options.push_back({ "*", "-mtprot, --mtp-requantize-output-tensor type", "Use output requantized to type for MTP (default: %s)", params.extra_output_type.c_str() });
|
||||
options.push_back({ "*", "-ctkd, --cache-type-k-draft TYPE", "KV cache data type for K for the draft model" });
|
||||
options.push_back({ "*", "-ctvd, --cache-type-v-draft TYPE", "KV cache data type for V for the draft model" });
|
||||
@@ -3274,9 +3274,10 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
|
||||
if (llama_supports_mmap()) {
|
||||
options.push_back({ "*", " --no-mmap", "do not memory-map model (slower load but may reduce pageouts if not using mlock)" });
|
||||
}
|
||||
options.push_back({ "*", " --run-time-repack", "repack tensors if interleaved variant is available"});
|
||||
options.push_back({ "*", " --cpu-moe", "keep all MoE weights in CPU memory"});
|
||||
options.push_back({ "*", " --n-cpu-moe N", "keep MoE weights of the first N layers in CPU memory"});
|
||||
options.push_back({ "*", "-rtr, --run-time-repack", "repack tensors if interleaved variant is available"});
|
||||
options.push_back({ "*", "-cmoe, --cpu-moe", "keep all MoE weights in CPU memory"});
|
||||
options.push_back({ "*", "-ncmoe, --n-cpu-moe N", "keep MoE weights of the first N layers in CPU memory"});
|
||||
options.push_back({ "*", "-thp, --transparent-huge-pages", "use transparent huge pages on Linux"});
|
||||
options.push_back({ "*", " --defer-experts", "defer expert mmap residency on Linux to reduce model load time"});
|
||||
options.push_back({ "*", " --prefetch-experts", "stream mmap'd MoE expert weights into the page cache on Linux"});
|
||||
options.push_back({ "*", " --prefetch-experts-threads N",
|
||||
@@ -3321,9 +3322,9 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
|
||||
options.push_back({ "model" });
|
||||
options.push_back({ "*", " --check-tensors", "check model tensor data for invalid values (default: %s)", params.check_tensors ? "true" : "false" });
|
||||
options.push_back({ "*", "-ot, --override-tensor NAME", "override tensor buffer type as tensor_name=buft, comma-separated" });
|
||||
options.push_back({ "*", " --override-kv KEY=TYPE:VALUE",
|
||||
"advanced option to override model metadata by key. may be specified multiple times.\n"
|
||||
"types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false" });
|
||||
options.push_back({ "*", "-okv, --override-kv KEY=TYPE:VALUE",
|
||||
"advanced option to override model metadata by key. may be specified multiple times.\n"
|
||||
"types: int, float, bool, str. example: --override-kv tokenizer.ggml.add_bos_token=bool:false" });
|
||||
options.push_back({ "*", " --lora FNAME", "apply LoRA adapter (can be repeated to use multiple adapters)" });
|
||||
options.push_back({ "*", " --lora-scaled FNAME S", "apply LoRA adapter with user defined scaling S (can be repeated to use multiple adapters)" });
|
||||
options.push_back({ "*", " --control-vector FNAME", "add a control vector\n"
|
||||
@@ -3372,7 +3373,7 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
|
||||
options.push_back({ "imatrix" });
|
||||
options.push_back({ "imatrix", "-o, --output FNAME", "output file (default: '%s')", params.out_file.c_str() });
|
||||
options.push_back({ "imatrix", " --output-draft FNAME", "paired draft output file (default: derived from --output)" });
|
||||
options.push_back({ "imatrix", " --output-frequency N", "output the imatrix every N iterations (default: %d)", params.n_out_freq });
|
||||
options.push_back({ "imatrix", "-ofreq, --output-frequency N", "output the imatrix every N iterations (default: %d)", params.n_out_freq });
|
||||
options.push_back({ "imatrix", " --save-frequency N", "save an imatrix copy every N iterations (default: %d)", params.n_save_freq });
|
||||
options.push_back({ "imatrix", " --process-output", "collect data for the output tensor (default: %s)", params.process_output ? "true" : "false" });
|
||||
options.push_back({ "imatrix", " --no-ppl", "do not compute perplexity (default: %s)", params.compute_ppl ? "true" : "false" });
|
||||
@@ -3389,9 +3390,9 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
|
||||
options.push_back({ "bench", " --output-format FORMAT", "output format: table, jsonl, or csv (default: table)" });
|
||||
|
||||
options.push_back({ "embedding" });
|
||||
options.push_back({ "embedding", " --embd-normalize", "normalisation for embendings (default: %d) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)", params.embd_normalize });
|
||||
options.push_back({ "embedding", " --embd-normalize", "normalisation for embeddings (default: %d) (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)", params.embd_normalize });
|
||||
options.push_back({ "embedding", " --embd-output-format", "empty = default, \"array\" = [[],[]...], \"json\" = openai style, \"json+\" = same \"json\" + cosine similarity matrix" });
|
||||
options.push_back({ "embedding", " --embd-separator", "separator of embendings (default \\n) for example \"<#sep#>\"" });
|
||||
options.push_back({ "embedding", " --embd-separator", "separator of embeddings (default \\n) for example \"<#sep#>\"" });
|
||||
|
||||
options.push_back({ "server" });
|
||||
options.push_back({ "server", " --host HOST", "ip address to listen (default: %s)", params.hostname.c_str() });
|
||||
@@ -3409,10 +3410,10 @@ void gpt_params_print_usage(int /*argc*/, char ** argv, const gpt_params & param
|
||||
options.push_back({ "server", " --api-key-file FNAME", "path to file containing API keys (default: none)" });
|
||||
options.push_back({ "server", " --ssl-key-file FNAME", "path to file a PEM-encoded SSL private key" });
|
||||
options.push_back({ "server", " --ssl-cert-file FNAME", "path to file a PEM-encoded SSL certificate" });
|
||||
options.push_back({ "server", " --timeout N", "server read/write timeout in seconds (default: %d)", params.timeout_read });
|
||||
options.push_back({ "server", "-to, --timeout N", "server read/write timeout in seconds (default: %d)", params.timeout_read });
|
||||
options.push_back({ "server", " --threads-http N", "number of threads used to process HTTP requests (default: %d)", params.n_threads_http });
|
||||
options.push_back({ "server", " --system-prompt-file FNAME",
|
||||
"set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications" });
|
||||
options.push_back({ "server", "-spf, --system-prompt-file FNAME",
|
||||
"set a file to load a system prompt (initial prompt of all slots), this is useful for chat applications" });
|
||||
options.push_back({ "server", " --log-format {text,json}",
|
||||
"log output format: json or text (default: json)" });
|
||||
options.push_back({ "server", " --metrics", "enable prometheus compatible metrics endpoint (default: %s)", params.endpoint_metrics ? "enabled" : "disabled" });
|
||||
|
||||
Reference in New Issue
Block a user