# Sample YAML file for configuration. | |
# Comment and uncomment values as needed. Every value has a default within the application. | |
# This file serves to be a drop in for config.yml | |
# Unless specified in the comments, DO NOT put these options in quotes! | |
# You can use https://www.yamllint.com/ if you want to check your YAML formatting. | |
# Options for networking | |
network: | |
# The IP to host on (default: 127.0.0.1). | |
# Use 0.0.0.0 to expose on all network adapters | |
host: 0.0.0.0 | |
# The port to host on (default: 5000) | |
port: 5000 | |
# Disable HTTP token authenticaion with requests | |
# WARNING: This will make your instance vulnerable! | |
# Turn on this option if you are ONLY connecting from localhost | |
disable_auth: False | |
# Options for logging | |
logging: | |
# Enable prompt logging (default: False) | |
prompt: False | |
# Enable generation parameter logging (default: False) | |
generation_params: False | |
# Options for sampling | |
sampling: | |
# Override preset name. Find this in the sampler-overrides folder (default: None) | |
# This overrides default fallbacks for sampler values that are passed to the API | |
# Server-side overrides are NOT needed by default | |
# WARNING: Using this can result in a generation speed penalty | |
#override_preset: | |
# Options for development and experimentation | |
developer: | |
# Skips exllamav2 version check (default: False) | |
# It's highly recommended to update your dependencies rather than enabling this flag | |
# WARNING: Don't set this unless you know what you're doing! | |
#unsafe_launch: False | |
# Disable all request streaming (default: False) | |
# A kill switch for turning off SSE in the API server | |
#disable_request_streaming: False | |
# Enable the torch CUDA malloc backend (default: False) | |
# This can save a few MBs of VRAM, but has a risk of errors. Use at your own risk. | |
cuda_malloc_backend: True | |
# Options for model overrides and loading | |
model: | |
# Overrides the directory to look for models (default: models) | |
# Windows users, DO NOT put this path in quotes! This directory will be invalid otherwise. | |
model_dir: models | |
# An initial model to load. Make sure the model is located in the model directory! | |
# A model can be loaded later via the API. | |
# REQUIRED: This must be filled out to load a model on startup! | |
model_name: Tess-v2.5.2-Qwen2-72B-safetensors_exl2_5.0bpw | |
# Sends dummy model names when the models endpoint is queried | |
# Enable this if the program is looking for a specific OAI model | |
#use_dummy_models: False | |
# The below parameters apply only if model_name is set | |
# Max sequence length (default: Empty) | |
# Fetched from the model's base sequence length in config.json by default | |
max_seq_len: 19968 | |
# Overrides base model context length (default: Empty) | |
# WARNING: Don't set this unless you know what you're doing! | |
# Again, do NOT use this for configuring context length, use max_seq_len above ^ | |
# Only use this if the model's base sequence length in config.json is incorrect (ex. Mistral 7B) | |
#override_base_seq_len: | |
# Automatically allocate resources to GPUs (default: True) | |
# NOTE: Not parsed for single GPU users | |
gpu_split_auto: True | |
# Reserve VRAM used for autosplit loading (default: 96 MB on GPU 0) | |
# This is represented as an array of MB per GPU used | |
autosplit_reserve: [6] | |
# An integer array of GBs of vram to split between GPUs (default: []) | |
# NOTE: Not parsed for single GPU users | |
#gpu_split: [20.6, 24] | |
# Rope scale (default: 1.0) | |
# Same thing as compress_pos_emb | |
# Only use if your model was trained on long context with rope (check config.json) | |
# Leave blank to pull the value from the model | |
#rope_scale: 1.0 | |
# Rope alpha (default: 1.0) | |
# Same thing as alpha_value | |
# Leave blank to automatically calculate alpha | |
#rope_alpha: 1.0 | |
# Disable Flash-attention 2. Set to True for GPUs lower than Nvidia's 3000 series. (default: False) | |
#no_flash_attention: False | |
# Enable different cache modes for VRAM savings (slight performance hit). | |
# Possible values FP16, FP8, Q4. (default: FP16) | |
cache_mode: Q4 | |
# Chunk size for prompt ingestion. A lower value reduces VRAM usage at the cost of ingestion speed (default: 2048) | |
# NOTE: Effects vary depending on the model. An ideal value is between 512 and 4096 | |
chunk_size: 2048 | |
# Set the prompt template for this model. If empty, attempts to look for the model's chat template. (default: None) | |
# If a model contains multiple templates in its tokenizer_config.json, set prompt_template to the name | |
# of the template you want to use.s | |
# NOTE: Only works with chat completion message lists! | |
#prompt_template: | |
# Number of experts to use PER TOKEN. Fetched from the model's config.json if not specified (default: Empty) | |
# WARNING: Don't set this unless you know what you're doing! | |
# NOTE: For MoE models (ex. Mixtral) only! | |
#num_experts_per_token: | |
# Enables CFG support (default: False) | |
# WARNING: This flag disables Flash Attention! (a stopgap fix until it's fixed in upstream) | |
#use_cfg: False | |
# Enables fasttensors to possibly increase model loading speeds (default: False) | |
#fasttensors: true | |
# Options for draft models (speculative decoding). This will use more VRAM! | |
#draft: | |
# Overrides the directory to look for draft (default: models) | |
#draft_model_dir: models | |
# An initial draft model to load. Make sure this model is located in the model directory! | |
# A draft model can be loaded later via the API. | |
#draft_model_name: A model name | |
# Rope scale for draft models (default: 1.0) | |
# Same thing as compress_pos_emb | |
# Only use if your draft model was trained on long context with rope (check config.json) | |
#draft_rope_scale: 1.0 | |
# Rope alpha for draft model (default: 1.0) | |
# Same thing as alpha_value | |
# Leave blank to automatically calculate alpha value | |
#draft_rope_alpha: 1.0 | |
# Options for loras | |
#lora: | |
# Overrides the directory to look for loras (default: loras) | |
#lora_dir: loras | |
# List of loras to load and associated scaling factors (default: 1.0). Comment out unused entries or add more rows as needed. | |
#loras: | |
#- name: lora1 | |
# scaling: 1.0 | |