533 líneas
42 KiB
Plaintext
533 líneas
42 KiB
Plaintext
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### Lllama.Cpp
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----- common params -----
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-h, --help, --usage print usage and exit
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--version show version and build info
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--license show source code license and dependencies
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-cl, --cache-list show list of models in cache
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--completion-bash print source-able bash completion script for llama.cpp
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--verbose-prompt print a verbose prompt before generation (default: false)
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-t, --threads N number of CPU threads to use during generation (default: -1)
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(env: LLAMA_ARG_THREADS)
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-tb, --threads-batch N number of threads to use during batch and prompt processing (default:
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same as --threads)
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-C, --cpu-mask M CPU affinity mask: arbitrarily long hex. Complements cpu-range
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(default: "")
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-Cr, --cpu-range lo-hi range of CPUs for affinity. Complements --cpu-mask
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--cpu-strict <0|1> use strict CPU placement (default: 0)
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--prio N set process/thread priority : low(-1), normal(0), medium(1), high(2),
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realtime(3) (default: 0)
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--poll <0...100> use polling level to wait for work (0 - no polling, default: 50)
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-Cb, --cpu-mask-batch M CPU affinity mask: arbitrarily long hex. Complements cpu-range-batch
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(default: same as --cpu-mask)
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-Crb, --cpu-range-batch lo-hi ranges of CPUs for affinity. Complements --cpu-mask-batch
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--cpu-strict-batch <0|1> use strict CPU placement (default: same as --cpu-strict)
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--prio-batch N set process/thread priority : 0-normal, 1-medium, 2-high, 3-realtime
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(default: 0)
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--poll-batch <0|1> use polling to wait for work (default: same as --poll)
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-c, --ctx-size N size of the prompt context (default: 0, 0 = loaded from model)
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(env: LLAMA_ARG_CTX_SIZE)
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-n, --predict, --n-predict N number of tokens to predict (default: -1, -1 = infinity)
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(env: LLAMA_ARG_N_PREDICT)
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-b, --batch-size N logical maximum batch size (default: 2048)
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(env: LLAMA_ARG_BATCH)
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-ub, --ubatch-size N physical maximum batch size (default: 512)
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(env: LLAMA_ARG_UBATCH)
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--keep N number of tokens to keep from the initial prompt (default: 0, -1 =
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all)
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--swa-full use full-size SWA cache (default: false)
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[(more
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info)](https://github.com/ggml-org/llama.cpp/pull/13194#issuecomment-2868343055)
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(env: LLAMA_ARG_SWA_FULL)
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-fa, --flash-attn [on|off|auto] set Flash Attention use ('on', 'off', or 'auto', default: 'auto')
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(env: LLAMA_ARG_FLASH_ATTN)
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--perf, --no-perf whether to enable internal libllama performance timings (default:
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false)
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(env: LLAMA_ARG_PERF)
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-e, --escape, --no-escape whether to process escapes sequences (\n, \r, \t, \', \", \\)
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(default: true)
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--rope-scaling {none,linear,yarn} RoPE frequency scaling method, defaults to linear unless specified by
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the model
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(env: LLAMA_ARG_ROPE_SCALING_TYPE)
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--rope-scale N RoPE context scaling factor, expands context by a factor of N
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(env: LLAMA_ARG_ROPE_SCALE)
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--rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: loaded from
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model)
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(env: LLAMA_ARG_ROPE_FREQ_BASE)
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--rope-freq-scale N RoPE frequency scaling factor, expands context by a factor of 1/N
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(env: LLAMA_ARG_ROPE_FREQ_SCALE)
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--yarn-orig-ctx N YaRN: original context size of model (default: 0 = model training
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context size)
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(env: LLAMA_ARG_YARN_ORIG_CTX)
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--yarn-ext-factor N YaRN: extrapolation mix factor (default: -1.00, 0.0 = full
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interpolation)
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(env: LLAMA_ARG_YARN_EXT_FACTOR)
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--yarn-attn-factor N YaRN: scale sqrt(t) or attention magnitude (default: -1.00)
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(env: LLAMA_ARG_YARN_ATTN_FACTOR)
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--yarn-beta-slow N YaRN: high correction dim or alpha (default: -1.00)
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(env: LLAMA_ARG_YARN_BETA_SLOW)
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--yarn-beta-fast N YaRN: low correction dim or beta (default: -1.00)
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(env: LLAMA_ARG_YARN_BETA_FAST)
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-kvo, --kv-offload, -nkvo, --no-kv-offload
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whether to enable KV cache offloading (default: enabled)
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(env: LLAMA_ARG_KV_OFFLOAD)
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--repack, -nr, --no-repack whether to enable weight repacking (default: enabled)
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(env: LLAMA_ARG_REPACK)
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--no-host bypass host buffer allowing extra buffers to be used
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(env: LLAMA_ARG_NO_HOST)
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-ctk, --cache-type-k TYPE KV cache data type for K
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allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
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(default: f16)
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(env: LLAMA_ARG_CACHE_TYPE_K)
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-ctv, --cache-type-v TYPE KV cache data type for V
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allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
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(default: f16)
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(env: LLAMA_ARG_CACHE_TYPE_V)
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-dt, --defrag-thold N KV cache defragmentation threshold (DEPRECATED)
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(env: LLAMA_ARG_DEFRAG_THOLD)
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--rpc SERVERS comma separated list of RPC servers (host:port)
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(env: LLAMA_ARG_RPC)
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--mlock force system to keep model in RAM rather than swapping or compressing
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(env: LLAMA_ARG_MLOCK)
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--mmap, --no-mmap whether to memory-map model. (if mmap disabled, slower load but may
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reduce pageouts if not using mlock) (default: enabled)
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(env: LLAMA_ARG_MMAP)
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-dio, --direct-io, -ndio, --no-direct-io
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use DirectIO if available. (default: disabled)
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(env: LLAMA_ARG_DIO)
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--numa TYPE attempt optimizations that help on some NUMA systems
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- distribute: spread execution evenly over all nodes
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- isolate: only spawn threads on CPUs on the node that execution
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started on
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- numactl: use the CPU map provided by numactl
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if run without this previously, it is recommended to drop the system
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page cache before using this
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see https://github.com/ggml-org/llama.cpp/issues/1437
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(env: LLAMA_ARG_NUMA)
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-dev, --device <dev1,dev2,..> comma-separated list of devices to use for offloading (none = don't
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offload)
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use --list-devices to see a list of available devices
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(env: LLAMA_ARG_DEVICE)
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--list-devices print list of available devices and exit
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-ot, --override-tensor <tensor name pattern>=<buffer type>,...
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override tensor buffer type
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(env: LLAMA_ARG_OVERRIDE_TENSOR)
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-cmoe, --cpu-moe keep all Mixture of Experts (MoE) weights in the CPU
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(env: LLAMA_ARG_CPU_MOE)
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-ncmoe, --n-cpu-moe N keep the Mixture of Experts (MoE) weights of the first N layers in the
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CPU
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(env: LLAMA_ARG_N_CPU_MOE)
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-ngl, --gpu-layers, --n-gpu-layers N max. number of layers to store in VRAM, either an exact number,
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'auto', or 'all' (default: auto)
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(env: LLAMA_ARG_N_GPU_LAYERS)
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-sm, --split-mode {none,layer,row} how to split the model across multiple GPUs, one of:
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- none: use one GPU only
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- layer (default): split layers and KV across GPUs
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- row: split rows across GPUs
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(env: LLAMA_ARG_SPLIT_MODE)
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-ts, --tensor-split N0,N1,N2,... fraction of the model to offload to each GPU, comma-separated list of
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proportions, e.g. 3,1
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(env: LLAMA_ARG_TENSOR_SPLIT)
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-mg, --main-gpu INDEX the GPU to use for the model (with split-mode = none), or for
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intermediate results and KV (with split-mode = row) (default: 0)
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(env: LLAMA_ARG_MAIN_GPU)
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-fit, --fit [on|off] whether to adjust unset arguments to fit in device memory ('on' or
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'off', default: 'on')
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(env: LLAMA_ARG_FIT)
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-fitt, --fit-target MiB0,MiB1,MiB2,...
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target margin per device for --fit, comma-separated list of values,
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single value is broadcast across all devices, default: 1024
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(env: LLAMA_ARG_FIT_TARGET)
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-fitc, --fit-ctx N minimum ctx size that can be set by --fit option, default: 4096
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(env: LLAMA_ARG_FIT_CTX)
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--check-tensors check model tensor data for invalid values (default: false)
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--override-kv KEY=TYPE:VALUE,... advanced option to override model metadata by key. to specify multiple
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overrides, either use comma-separated values.
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types: int, float, bool, str. example: --override-kv
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tokenizer.ggml.add_bos_token=bool:false,tokenizer.ggml.add_eos_token=bool:false
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--op-offload, --no-op-offload whether to offload host tensor operations to device (default: true)
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--lora FNAME path to LoRA adapter (use comma-separated values to load multiple
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adapters)
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--lora-scaled FNAME:SCALE,... path to LoRA adapter with user defined scaling (format:
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FNAME:SCALE,...)
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note: use comma-separated values
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--control-vector FNAME add a control vector
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note: use comma-separated values to add multiple control vectors
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--control-vector-scaled FNAME:SCALE,...
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add a control vector with user defined scaling SCALE
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note: use comma-separated values (format: FNAME:SCALE,...)
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--control-vector-layer-range START END
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layer range to apply the control vector(s) to, start and end inclusive
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-m, --model FNAME model path to load
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(env: LLAMA_ARG_MODEL)
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-mu, --model-url MODEL_URL model download url (default: unused)
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(env: LLAMA_ARG_MODEL_URL)
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-dr, --docker-repo [<repo>/]<model>[:quant]
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Docker Hub model repository. repo is optional, default to ai/. quant
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is optional, default to :latest.
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example: gemma3
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(default: unused)
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(env: LLAMA_ARG_DOCKER_REPO)
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-hf, -hfr, --hf-repo <user>/<model>[:quant]
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Hugging Face model repository; quant is optional, case-insensitive,
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default to Q4_K_M, or falls back to the first file in the repo if
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Q4_K_M doesn't exist.
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mmproj is also downloaded automatically if available. to disable, add
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--no-mmproj
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example: unsloth/phi-4-GGUF:q4_k_m
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(default: unused)
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(env: LLAMA_ARG_HF_REPO)
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-hfd, -hfrd, --hf-repo-draft <user>/<model>[:quant]
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Same as --hf-repo, but for the draft model (default: unused)
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(env: LLAMA_ARG_HFD_REPO)
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-hff, --hf-file FILE Hugging Face model file. If specified, it will override the quant in
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--hf-repo (default: unused)
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(env: LLAMA_ARG_HF_FILE)
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-hfv, -hfrv, --hf-repo-v <user>/<model>[:quant]
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Hugging Face model repository for the vocoder model (default: unused)
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(env: LLAMA_ARG_HF_REPO_V)
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-hffv, --hf-file-v FILE Hugging Face model file for the vocoder model (default: unused)
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(env: LLAMA_ARG_HF_FILE_V)
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-hft, --hf-token TOKEN Hugging Face access token (default: value from HF_TOKEN environment
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variable)
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(env: HF_TOKEN)
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--log-disable Log disable
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--log-file FNAME Log to file
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(env: LLAMA_LOG_FILE)
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--log-colors [on|off|auto] Set colored logging ('on', 'off', or 'auto', default: 'auto')
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'auto' enables colors when output is to a terminal
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(env: LLAMA_LOG_COLORS)
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-v, --verbose, --log-verbose Set verbosity level to infinity (i.e. log all messages, useful for
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debugging)
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--offline Offline mode: forces use of cache, prevents network access
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(env: LLAMA_OFFLINE)
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-lv, --verbosity, --log-verbosity N Set the verbosity threshold. Messages with a higher verbosity will be
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ignored. Values:
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- 0: generic output
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- 1: error
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- 2: warning
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- 3: info
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- 4: debug
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(default: 3)
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(env: LLAMA_LOG_VERBOSITY)
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--log-prefix Enable prefix in log messages
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(env: LLAMA_LOG_PREFIX)
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--log-timestamps Enable timestamps in log messages
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(env: LLAMA_LOG_TIMESTAMPS)
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-ctkd, --cache-type-k-draft TYPE KV cache data type for K for the draft model
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allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
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(default: f16)
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(env: LLAMA_ARG_CACHE_TYPE_K_DRAFT)
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-ctvd, --cache-type-v-draft TYPE KV cache data type for V for the draft model
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allowed values: f32, f16, bf16, q8_0, q4_0, q4_1, iq4_nl, q5_0, q5_1
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(default: f16)
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(env: LLAMA_ARG_CACHE_TYPE_V_DRAFT)
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----- sampling params -----
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--samplers SAMPLERS samplers that will be used for generation in the order, separated by
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';'
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(default:
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penalties;dry;top_n_sigma;top_k;typ_p;top_p;min_p;xtc;temperature)
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-s, --seed SEED RNG seed (default: -1, use random seed for -1)
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--sampler-seq, --sampling-seq SEQUENCE
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simplified sequence for samplers that will be used (default:
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edskypmxt)
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--ignore-eos ignore end of stream token and continue generating (implies
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--logit-bias EOS-inf)
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--temp N temperature (default: 0.80)
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--top-k N top-k sampling (default: 40, 0 = disabled)
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(env: LLAMA_ARG_TOP_K)
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--top-p N top-p sampling (default: 0.95, 1.0 = disabled)
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--min-p N min-p sampling (default: 0.05, 0.0 = disabled)
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--top-nsigma N top-n-sigma sampling (default: -1.00, -1.0 = disabled)
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--xtc-probability N xtc probability (default: 0.00, 0.0 = disabled)
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--xtc-threshold N xtc threshold (default: 0.10, 1.0 = disabled)
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--typical N locally typical sampling, parameter p (default: 1.00, 1.0 = disabled)
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--repeat-last-n N last n tokens to consider for penalize (default: 64, 0 = disabled, -1
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= ctx_size)
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--repeat-penalty N penalize repeat sequence of tokens (default: 1.00, 1.0 = disabled)
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--presence-penalty N repeat alpha presence penalty (default: 0.00, 0.0 = disabled)
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--frequency-penalty N repeat alpha frequency penalty (default: 0.00, 0.0 = disabled)
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--dry-multiplier N set DRY sampling multiplier (default: 0.00, 0.0 = disabled)
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--dry-base N set DRY sampling base value (default: 1.75)
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--dry-allowed-length N set allowed length for DRY sampling (default: 2)
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--dry-penalty-last-n N set DRY penalty for the last n tokens (default: -1, 0 = disable, -1 =
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context size)
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--dry-sequence-breaker STRING add sequence breaker for DRY sampling, clearing out default breakers
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('\n', ':', '"', '*') in the process; use "none" to not use any
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sequence breakers
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--adaptive-target N adaptive-p: select tokens near this probability (valid range 0.0 to
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1.0; negative = disabled) (default: -1.00)
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[(more info)](https://github.com/ggml-org/llama.cpp/pull/17927)
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--adaptive-decay N adaptive-p: decay rate for target adaptation over time. lower values
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are more reactive, higher values are more stable.
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(valid range 0.0 to 0.99) (default: 0.90)
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--dynatemp-range N dynamic temperature range (default: 0.00, 0.0 = disabled)
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--dynatemp-exp N dynamic temperature exponent (default: 1.00)
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--mirostat N use Mirostat sampling.
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Top K, Nucleus and Locally Typical samplers are ignored if used.
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(default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
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--mirostat-lr N Mirostat learning rate, parameter eta (default: 0.10)
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--mirostat-ent N Mirostat target entropy, parameter tau (default: 5.00)
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-l, --logit-bias TOKEN_ID(+/-)BIAS modifies the likelihood of token appearing in the completion,
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|
|
i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',
|
||
|
|
or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'
|
||
|
|
--grammar GRAMMAR BNF-like grammar to constrain generations (see samples in grammars/
|
||
|
|
dir) (default: '')
|
||
|
|
--grammar-file FNAME file to read grammar from
|
||
|
|
-j, --json-schema SCHEMA JSON schema to constrain generations (https://json-schema.org/), e.g.
|
||
|
|
`{}` for any JSON object
|
||
|
|
For schemas w/ external $refs, use --grammar +
|
||
|
|
example/json_schema_to_grammar.py instead
|
||
|
|
-jf, --json-schema-file FILE File containing a JSON schema to constrain generations
|
||
|
|
(https://json-schema.org/), e.g. `{}` for any JSON object
|
||
|
|
For schemas w/ external $refs, use --grammar +
|
||
|
|
example/json_schema_to_grammar.py instead
|
||
|
|
-bs, --backend-sampling enable backend sampling (experimental) (default: disabled)
|
||
|
|
(env: LLAMA_ARG_BACKEND_SAMPLING)
|
||
|
|
|
||
|
|
|
||
|
|
----- example-specific params -----
|
||
|
|
|
||
|
|
-lcs, --lookup-cache-static FNAME path to static lookup cache to use for lookup decoding (not updated by
|
||
|
|
generation)
|
||
|
|
-lcd, --lookup-cache-dynamic FNAME path to dynamic lookup cache to use for lookup decoding (updated by
|
||
|
|
generation)
|
||
|
|
--ctx-checkpoints, --swa-checkpoints N
|
||
|
|
max number of context checkpoints to create per slot (default:
|
||
|
|
8)[(more info)](https://github.com/ggml-org/llama.cpp/pull/15293)
|
||
|
|
(env: LLAMA_ARG_CTX_CHECKPOINTS)
|
||
|
|
-cram, --cache-ram N set the maximum cache size in MiB (default: 8192, -1 - no limit, 0 -
|
||
|
|
disable)[(more
|
||
|
|
info)](https://github.com/ggml-org/llama.cpp/pull/16391)
|
||
|
|
(env: LLAMA_ARG_CACHE_RAM)
|
||
|
|
-kvu, --kv-unified, -no-kvu, --no-kv-unified
|
||
|
|
use single unified KV buffer shared across all sequences (default:
|
||
|
|
enabled if number of slots is auto)
|
||
|
|
(env: LLAMA_ARG_KV_UNIFIED)
|
||
|
|
--context-shift, --no-context-shift whether to use context shift on infinite text generation (default:
|
||
|
|
disabled)
|
||
|
|
(env: LLAMA_ARG_CONTEXT_SHIFT)
|
||
|
|
-r, --reverse-prompt PROMPT halt generation at PROMPT, return control in interactive mode
|
||
|
|
-sp, --special special tokens output enabled (default: false)
|
||
|
|
--warmup, --no-warmup whether to perform warmup with an empty run (default: enabled)
|
||
|
|
--spm-infill use Suffix/Prefix/Middle pattern for infill (instead of
|
||
|
|
Prefix/Suffix/Middle) as some models prefer this. (default: disabled)
|
||
|
|
--pooling {none,mean,cls,last,rank} pooling type for embeddings, use model default if unspecified
|
||
|
|
(env: LLAMA_ARG_POOLING)
|
||
|
|
-np, --parallel N number of server slots (default: -1, -1 = auto)
|
||
|
|
(env: LLAMA_ARG_N_PARALLEL)
|
||
|
|
-cb, --cont-batching, -nocb, --no-cont-batching
|
||
|
|
whether to enable continuous batching (a.k.a dynamic batching)
|
||
|
|
(default: enabled)
|
||
|
|
(env: LLAMA_ARG_CONT_BATCHING)
|
||
|
|
-mm, --mmproj FILE path to a multimodal projector file. see tools/mtmd/README.md
|
||
|
|
note: if -hf is used, this argument can be omitted
|
||
|
|
(env: LLAMA_ARG_MMPROJ)
|
||
|
|
-mmu, --mmproj-url URL URL to a multimodal projector file. see tools/mtmd/README.md
|
||
|
|
(env: LLAMA_ARG_MMPROJ_URL)
|
||
|
|
--mmproj-auto, --no-mmproj, --no-mmproj-auto
|
||
|
|
whether to use multimodal projector file (if available), useful when
|
||
|
|
using -hf (default: enabled)
|
||
|
|
(env: LLAMA_ARG_MMPROJ_AUTO)
|
||
|
|
--mmproj-offload, --no-mmproj-offload whether to enable GPU offloading for multimodal projector (default:
|
||
|
|
enabled)
|
||
|
|
(env: LLAMA_ARG_MMPROJ_OFFLOAD)
|
||
|
|
--image-min-tokens N minimum number of tokens each image can take, only used by vision
|
||
|
|
models with dynamic resolution (default: read from model)
|
||
|
|
(env: LLAMA_ARG_IMAGE_MIN_TOKENS)
|
||
|
|
--image-max-tokens N maximum number of tokens each image can take, only used by vision
|
||
|
|
models with dynamic resolution (default: read from model)
|
||
|
|
(env: LLAMA_ARG_IMAGE_MAX_TOKENS)
|
||
|
|
-otd, --override-tensor-draft <tensor name pattern>=<buffer type>,...
|
||
|
|
override tensor buffer type for draft model
|
||
|
|
-cmoed, --cpu-moe-draft keep all Mixture of Experts (MoE) weights in the CPU for the draft
|
||
|
|
model
|
||
|
|
(env: LLAMA_ARG_CPU_MOE_DRAFT)
|
||
|
|
-ncmoed, --n-cpu-moe-draft N keep the Mixture of Experts (MoE) weights of the first N layers in the
|
||
|
|
CPU for the draft model
|
||
|
|
(env: LLAMA_ARG_N_CPU_MOE_DRAFT)
|
||
|
|
-a, --alias STRING set alias for model name (to be used by REST API)
|
||
|
|
(env: LLAMA_ARG_ALIAS)
|
||
|
|
--host HOST ip address to listen, or bind to an UNIX socket if the address ends
|
||
|
|
with .sock (default: 127.0.0.1)
|
||
|
|
(env: LLAMA_ARG_HOST)
|
||
|
|
--port PORT port to listen (default: 8080)
|
||
|
|
(env: LLAMA_ARG_PORT)
|
||
|
|
--path PATH path to serve static files from (default: )
|
||
|
|
(env: LLAMA_ARG_STATIC_PATH)
|
||
|
|
--api-prefix PREFIX prefix path the server serves from, without the trailing slash
|
||
|
|
(default: )
|
||
|
|
(env: LLAMA_ARG_API_PREFIX)
|
||
|
|
--webui-config JSON JSON that provides default WebUI settings (overrides WebUI defaults)
|
||
|
|
(env: LLAMA_ARG_WEBUI_CONFIG)
|
||
|
|
--webui-config-file PATH JSON file that provides default WebUI settings (overrides WebUI
|
||
|
|
defaults)
|
||
|
|
(env: LLAMA_ARG_WEBUI_CONFIG_FILE)
|
||
|
|
--webui, --no-webui whether to enable the Web UI (default: enabled)
|
||
|
|
(env: LLAMA_ARG_WEBUI)
|
||
|
|
--embedding, --embeddings restrict to only support embedding use case; use only with dedicated
|
||
|
|
embedding models (default: disabled)
|
||
|
|
(env: LLAMA_ARG_EMBEDDINGS)
|
||
|
|
--rerank, --reranking enable reranking endpoint on server (default: disabled)
|
||
|
|
(env: LLAMA_ARG_RERANKING)
|
||
|
|
--api-key KEY API key to use for authentication, multiple keys can be provided as a
|
||
|
|
comma-separated list (default: none)
|
||
|
|
(env: LLAMA_API_KEY)
|
||
|
|
--api-key-file FNAME path to file containing API keys (default: none)
|
||
|
|
--ssl-key-file FNAME path to file a PEM-encoded SSL private key
|
||
|
|
(env: LLAMA_ARG_SSL_KEY_FILE)
|
||
|
|
--ssl-cert-file FNAME path to file a PEM-encoded SSL certificate
|
||
|
|
(env: LLAMA_ARG_SSL_CERT_FILE)
|
||
|
|
--chat-template-kwargs STRING sets additional params for the json template parser, must be a valid
|
||
|
|
json object string, e.g. '{"key1":"value1","key2":"value2"}'
|
||
|
|
(env: LLAMA_CHAT_TEMPLATE_KWARGS)
|
||
|
|
-to, --timeout N server read/write timeout in seconds (default: 600)
|
||
|
|
(env: LLAMA_ARG_TIMEOUT)
|
||
|
|
--threads-http N number of threads used to process HTTP requests (default: -1)
|
||
|
|
(env: LLAMA_ARG_THREADS_HTTP)
|
||
|
|
--cache-prompt, --no-cache-prompt whether to enable prompt caching (default: enabled)
|
||
|
|
(env: LLAMA_ARG_CACHE_PROMPT)
|
||
|
|
--cache-reuse N min chunk size to attempt reusing from the cache via KV shifting,
|
||
|
|
requires prompt caching to be enabled (default: 0)
|
||
|
|
[(card)](https://ggml.ai/f0.png)
|
||
|
|
(env: LLAMA_ARG_CACHE_REUSE)
|
||
|
|
--metrics enable prometheus compatible metrics endpoint (default: disabled)
|
||
|
|
(env: LLAMA_ARG_ENDPOINT_METRICS)
|
||
|
|
--props enable changing global properties via POST /props (default: disabled)
|
||
|
|
(env: LLAMA_ARG_ENDPOINT_PROPS)
|
||
|
|
--slots, --no-slots expose slots monitoring endpoint (default: enabled)
|
||
|
|
(env: LLAMA_ARG_ENDPOINT_SLOTS)
|
||
|
|
--slot-save-path PATH path to save slot kv cache (default: disabled)
|
||
|
|
--media-path PATH directory for loading local media files; files can be accessed via
|
||
|
|
file:// URLs using relative paths (default: disabled)
|
||
|
|
--models-dir PATH directory containing models for the router server (default: disabled)
|
||
|
|
(env: LLAMA_ARG_MODELS_DIR)
|
||
|
|
--models-preset PATH path to INI file containing model presets for the router server
|
||
|
|
(default: disabled)
|
||
|
|
(env: LLAMA_ARG_MODELS_PRESET)
|
||
|
|
--models-max N for router server, maximum number of models to load simultaneously
|
||
|
|
(default: 4, 0 = unlimited)
|
||
|
|
(env: LLAMA_ARG_MODELS_MAX)
|
||
|
|
--models-autoload, --no-models-autoload
|
||
|
|
for router server, whether to automatically load models (default:
|
||
|
|
enabled)
|
||
|
|
(env: LLAMA_ARG_MODELS_AUTOLOAD)
|
||
|
|
--jinja, --no-jinja whether to use jinja template engine for chat (default: enabled)
|
||
|
|
(env: LLAMA_ARG_JINJA)
|
||
|
|
--reasoning-format FORMAT controls whether thought tags are allowed and/or extracted from the
|
||
|
|
response, and in which format they're returned; one of:
|
||
|
|
- none: leaves thoughts unparsed in `message.content`
|
||
|
|
- deepseek: puts thoughts in `message.reasoning_content`
|
||
|
|
- deepseek-legacy: keeps `<think>` tags in `message.content` while
|
||
|
|
also populating `message.reasoning_content`
|
||
|
|
(default: auto)
|
||
|
|
(env: LLAMA_ARG_THINK)
|
||
|
|
--reasoning-budget N controls the amount of thinking allowed; currently only one of: -1 for
|
||
|
|
unrestricted thinking budget, or 0 to disable thinking (default: -1)
|
||
|
|
(env: LLAMA_ARG_THINK_BUDGET)
|
||
|
|
--chat-template JINJA_TEMPLATE set custom jinja chat template (default: template taken from model's
|
||
|
|
metadata)
|
||
|
|
if suffix/prefix are specified, template will be disabled
|
||
|
|
only commonly used templates are accepted (unless --jinja is set
|
||
|
|
before this flag):
|
||
|
|
list of built-in templates:
|
||
|
|
bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml,
|
||
|
|
command-r, deepseek, deepseek2, deepseek3, exaone-moe, exaone3,
|
||
|
|
exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, grok-2,
|
||
|
|
hunyuan-dense, hunyuan-moe, kimi-k2, llama2, llama2-sys,
|
||
|
|
llama2-sys-bos, llama2-sys-strip, llama3, llama4, megrez, minicpm,
|
||
|
|
mistral-v1, mistral-v3, mistral-v3-tekken, mistral-v7,
|
||
|
|
mistral-v7-tekken, monarch, openchat, orion, pangu-embedded, phi3,
|
||
|
|
phi4, rwkv-world, seed_oss, smolvlm, solar-open, vicuna, vicuna-orca,
|
||
|
|
yandex, zephyr
|
||
|
|
(env: LLAMA_ARG_CHAT_TEMPLATE)
|
||
|
|
--chat-template-file JINJA_TEMPLATE_FILE
|
||
|
|
set custom jinja chat template file (default: template taken from
|
||
|
|
model's metadata)
|
||
|
|
if suffix/prefix are specified, template will be disabled
|
||
|
|
only commonly used templates are accepted (unless --jinja is set
|
||
|
|
before this flag):
|
||
|
|
list of built-in templates:
|
||
|
|
bailing, bailing-think, bailing2, chatglm3, chatglm4, chatml,
|
||
|
|
command-r, deepseek, deepseek2, deepseek3, exaone-moe, exaone3,
|
||
|
|
exaone4, falcon3, gemma, gigachat, glmedge, gpt-oss, granite, grok-2,
|
||
|
|
hunyuan-dense, hunyuan-moe, kimi-k2, llama2, llama2-sys,
|
||
|
|
llama2-sys-bos, llama2-sys-strip, llama3, llama4, megrez, minicpm,
|
||
|
|
mistral-v1, mistral-v3, mistral-v3-tekken, mistral-v7,
|
||
|
|
mistral-v7-tekken, monarch, openchat, orion, pangu-embedded, phi3,
|
||
|
|
phi4, rwkv-world, seed_oss, smolvlm, solar-open, vicuna, vicuna-orca,
|
||
|
|
yandex, zephyr
|
||
|
|
(env: LLAMA_ARG_CHAT_TEMPLATE_FILE)
|
||
|
|
--prefill-assistant, --no-prefill-assistant
|
||
|
|
whether to prefill the assistant's response if the last message is an
|
||
|
|
assistant message (default: prefill enabled)
|
||
|
|
when this flag is set, if the last message is an assistant message
|
||
|
|
then it will be treated as a full message and not prefilled
|
||
|
|
|
||
|
|
(env: LLAMA_ARG_PREFILL_ASSISTANT)
|
||
|
|
-sps, --slot-prompt-similarity SIMILARITY
|
||
|
|
how much the prompt of a request must match the prompt of a slot in
|
||
|
|
order to use that slot (default: 0.10, 0.0 = disabled)
|
||
|
|
--lora-init-without-apply load LoRA adapters without applying them (apply later via POST
|
||
|
|
/lora-adapters) (default: disabled)
|
||
|
|
--sleep-idle-seconds SECONDS number of seconds of idleness after which the server will sleep
|
||
|
|
(default: -1; -1 = disabled)
|
||
|
|
-td, --threads-draft N number of threads to use during generation (default: same as
|
||
|
|
--threads)
|
||
|
|
-tbd, --threads-batch-draft N number of threads to use during batch and prompt processing (default:
|
||
|
|
same as --threads-draft)
|
||
|
|
--draft, --draft-n, --draft-max N number of tokens to draft for speculative decoding (default: 16)
|
||
|
|
(env: LLAMA_ARG_DRAFT_MAX)
|
||
|
|
--draft-min, --draft-n-min N minimum number of draft tokens to use for speculative decoding
|
||
|
|
(default: 0)
|
||
|
|
(env: LLAMA_ARG_DRAFT_MIN)
|
||
|
|
--draft-p-min P minimum speculative decoding probability (greedy) (default: 0.75)
|
||
|
|
(env: LLAMA_ARG_DRAFT_P_MIN)
|
||
|
|
-cd, --ctx-size-draft N size of the prompt context for the draft model (default: 0, 0 = loaded
|
||
|
|
from model)
|
||
|
|
(env: LLAMA_ARG_CTX_SIZE_DRAFT)
|
||
|
|
-devd, --device-draft <dev1,dev2,..> comma-separated list of devices to use for offloading the draft model
|
||
|
|
(none = don't offload)
|
||
|
|
use --list-devices to see a list of available devices
|
||
|
|
-ngld, --gpu-layers-draft, --n-gpu-layers-draft N
|
||
|
|
max. number of draft model layers to store in VRAM, either an exact
|
||
|
|
number, 'auto', or 'all' (default: auto)
|
||
|
|
(env: LLAMA_ARG_N_GPU_LAYERS_DRAFT)
|
||
|
|
-md, --model-draft FNAME draft model for speculative decoding (default: unused)
|
||
|
|
(env: LLAMA_ARG_MODEL_DRAFT)
|
||
|
|
--spec-replace TARGET DRAFT translate the string in TARGET into DRAFT if the draft model and main
|
||
|
|
model are not compatible
|
||
|
|
--spec-type [none|ngram-cache|ngram-simple|ngram-map-k|ngram-map-k4v|ngram-mod]
|
||
|
|
type of speculative decoding to use when no draft model is provided
|
||
|
|
(default: none)
|
||
|
|
--spec-ngram-size-n N ngram size N for ngram-simple/ngram-map speculative decoding, length
|
||
|
|
of lookup n-gram (default: 12)
|
||
|
|
--spec-ngram-size-m N ngram size M for ngram-simple/ngram-map speculative decoding, length
|
||
|
|
of draft m-gram (default: 48)
|
||
|
|
--spec-ngram-min-hits N minimum hits for ngram-map speculative decoding (default: 1)
|
||
|
|
-mv, --model-vocoder FNAME vocoder model for audio generation (default: unused)
|
||
|
|
--tts-use-guide-tokens Use guide tokens to improve TTS word recall
|
||
|
|
--embd-gemma-default use default EmbeddingGemma model (note: can download weights from the
|
||
|
|
internet)
|
||
|
|
--fim-qwen-1.5b-default use default Qwen 2.5 Coder 1.5B (note: can download weights from the
|
||
|
|
internet)
|
||
|
|
--fim-qwen-3b-default use default Qwen 2.5 Coder 3B (note: can download weights from the
|
||
|
|
internet)
|
||
|
|
--fim-qwen-7b-default use default Qwen 2.5 Coder 7B (note: can download weights from the
|
||
|
|
internet)
|
||
|
|
--fim-qwen-7b-spec use Qwen 2.5 Coder 7B + 0.5B draft for speculative decoding (note: can
|
||
|
|
download weights from the internet)
|
||
|
|
--fim-qwen-14b-spec use Qwen 2.5 Coder 14B + 0.5B draft for speculative decoding (note:
|
||
|
|
can download weights from the internet)
|
||
|
|
--fim-qwen-30b-default use default Qwen 3 Coder 30B A3B Instruct (note: can download weights
|
||
|
|
from the internet)
|
||
|
|
--gpt-oss-20b-default use gpt-oss-20b (note: can download weights from the internet)
|
||
|
|
--gpt-oss-120b-default use gpt-oss-120b (note: can download weights from the internet)
|
||
|
|
--vision-gemma-4b-default use Gemma 3 4B QAT (note: can download weights from the internet)
|
||
|
|
--vision-gemma-12b-default use Gemma 3 12B QAT (note: can download weights from the internet)
|