# Sample YAML file for configuration. # Comment out values as needed. Every value has a default within the application. # 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: 127.0.0.1 # 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 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. model_name: A model name # 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: None) # Fetched from the model's base sequence length in config.json by default max_seq_len: # Overrides base model context length (default: None) # WARNING: Don't set this unless you know what you're doing! # Only use this if the model's base sequence length in config.json is incorrect (ex. Mistral/Mixtral models) override_base_seq_len: # Automatically allocate resources to GPUs (default: True) gpu_split_auto: True # An integer array of GBs of vram to split between GPUs (default: []) 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) 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 8 bit cache mode for VRAM savings (slight performance hit). Possible values FP16, FP8. (default: FP16) cache_mode: FP16 # Set the prompt template for this model. If empty, chat completions will be disabled. (default: None) # NOTE: Only works with chat completion message lists! prompt_template: # Number of experts to use per token. Loads from the model's config.json if not specified (default: None) # WARNING: Don't set this unless you know what you're doing! # NOTE: For MoE models (ex. Mixtral) only! num_experts_per_token: # 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 - name: lora2 scaling: 0.9 - name: lora3 scaling: 0.5