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Upload tabbyAPI config.yml

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+ # Sample YAML file for configuration.
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+ # Comment and uncomment values as needed.
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+ # Every value has a default within the application.
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+ # This file serves to be a drop in for config.yml
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+
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+ # Unless specified in the comments, DO NOT put these options in quotes!
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+ # You can use https://www.yamllint.com/ if you want to check your YAML formatting.
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+
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+ # Options for networking
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+ network:
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+ # The IP to host on (default: 127.0.0.1).
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+ # Use 0.0.0.0 to expose on all network adapters.
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+ host: 127.0.0.1
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+
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+ # The port to host on (default: 5000).
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+ port: 5000
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+
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+ # Disable HTTP token authentication with requests.
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+ # WARNING: This will make your instance vulnerable!
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+ # Turn on this option if you are ONLY connecting from localhost.
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+ disable_auth: false
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+
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+ # Send tracebacks over the API (default: False).
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+ # NOTE: Only enable this for debug purposes.
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+ send_tracebacks: false
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+
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+ # Select API servers to enable (default: ["OAI"]).
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+ # Possible values: OAI, Kobold.
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+ api_servers: ["OAI"]
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+
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+ # Options for logging
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+ logging:
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+ # Enable prompt logging (default: False).
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+ log_prompt: false
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+
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+ # Enable generation parameter logging (default: False).
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+ log_generation_params: false
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+
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+ # Enable request logging (default: False).
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+ # NOTE: Only use this for debugging!
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+ log_requests: false
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+
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+ # Options for model overrides and loading
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+ # Please read the comments to understand how arguments are handled
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+ # between initial and API loads
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+ model:
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+ # Directory to look for models (default: models).
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+ # Windows users, do NOT put this path in quotes!
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+ model_dir: models
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+
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+ # Allow direct loading of models from a completion or chat completion request (default: False).
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+ # This method of loading is strict by default.
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+ # Enable dummy models to add exceptions for invalid model names.
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+ inline_model_loading: false
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+
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+ # Sends dummy model names when the models endpoint is queried. (default: False)
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+ # Enable this if the client is looking for specific OAI models.
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+ use_dummy_models: false
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+
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+ # A list of fake model names that are sent via the /v1/models endpoint. (default: ["gpt-3.5-turbo"])
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+ # Also used as bypasses for strict mode if inline_model_loading is true.
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+ dummy_model_names: ["gpt-3.5-turbo"]
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+
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+ # An initial model to load.
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+ # Make sure the model is located in the model directory!
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+ # REQUIRED: This must be filled out to load a model on startup.
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+ ################################################################################
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+ model_name: wolfram_Mistral-Large-Instruct-2411-2.75bpw-h6-exl2
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+ ################################################################################
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+
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+ # Names of args to use as a fallback for API load requests (default: []).
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+ # For example, if you always want cache_mode to be Q4 instead of on the inital model load, add "cache_mode" to this array.
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+ # Example: ['max_seq_len', 'cache_mode'].
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+ use_as_default: []
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+
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+ # Max sequence length (default: Empty).
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+ # Fetched from the model's base sequence length in config.json by default.
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+ ################################################################################
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+ max_seq_len: 32768 # /131072
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+ ################################################################################
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+
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+ # Load model with tensor parallelism.
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+ # Falls back to autosplit if GPU split isn't provided.
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+ # This ignores the gpu_split_auto value.
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+ tensor_parallel: false
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+
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+ # Automatically allocate resources to GPUs (default: True).
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+ # Not parsed for single GPU users.
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+ gpu_split_auto: true
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+
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+ # Reserve VRAM used for autosplit loading (default: 96 MB on GPU 0).
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+ # Represented as an array of MB per GPU.
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+ autosplit_reserve: [96]
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+
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+ # An integer array of GBs of VRAM to split between GPUs (default: []).
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+ # Used with tensor parallelism.
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+ gpu_split: []
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+
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+ # Rope scale (default: 1.0).
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+ # Same as compress_pos_emb.
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+ # Use if the model was trained on long context with rope.
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+ # Leave blank to pull the value from the model.
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+ rope_scale: 1.0
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+
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+ # Rope alpha (default: None).
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+ # Same as alpha_value. Set to "auto" to auto-calculate.
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+ # Leaving this value blank will either pull from the model or auto-calculate.
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+ rope_alpha:
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+
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+ # Enable different cache modes for VRAM savings (default: FP16).
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+ # Possible values: 'FP16', 'Q8', 'Q6', 'Q4'.
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+ ################################################################################
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+ cache_mode: Q4
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+ ################################################################################
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+
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+ # Size of the prompt cache to allocate (default: max_seq_len).
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+ # Must be a multiple of 256 and can't be less than max_seq_len.
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+ # For CFG, set this to 2 * max_seq_len.
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+ cache_size:
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+
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+ # Chunk size for prompt ingestion (default: 2048).
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+ # A lower value reduces VRAM usage but decreases ingestion speed.
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+ # NOTE: Effects vary depending on the model.
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+ # An ideal value is between 512 and 4096.
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+ chunk_size: 2048
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+
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+ # Set the maximum number of prompts to process at one time (default: None/Automatic).
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+ # Automatically calculated if left blank.
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+ # NOTE: Only available for Nvidia ampere (30 series) and above GPUs.
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+ max_batch_size:
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+
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+ # Set the prompt template for this model. (default: None)
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+ # If empty, attempts to look for the model's chat template.
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+ # If a model contains multiple templates in its tokenizer_config.json,
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+ # set prompt_template to the name of the template you want to use.
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+ # NOTE: Only works with chat completion message lists!
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+ prompt_template:
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+
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+ # Number of experts to use per token.
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+ # Fetched from the model's config.json if empty.
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+ # NOTE: For MoE models only.
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+ # WARNING: Don't set this unless you know what you're doing!
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+ num_experts_per_token:
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+
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+ # Options for draft models (speculative decoding)
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+ # This will use more VRAM!
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+ draft_model:
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+ # Directory to look for draft models (default: models)
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+ draft_model_dir: models
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+
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+ # An initial draft model to load.
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+ # Ensure the model is in the model directory.
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+ draft_model_name:
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+
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+ # Rope scale for draft models (default: 1.0).
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+ # Same as compress_pos_emb.
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+ # Use if the draft model was trained on long context with rope.
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+ draft_rope_scale: 1.0
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+
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+ # Rope alpha for draft models (default: None).
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+ # Same as alpha_value. Set to "auto" to auto-calculate.
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+ # Leaving this value blank will either pull from the model or auto-calculate.
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+ draft_rope_alpha:
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+
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+ # Cache mode for draft models to save VRAM (default: FP16).
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+ # Possible values: 'FP16', 'Q8', 'Q6', 'Q4'.
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+ draft_cache_mode: FP16
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+
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+ # Options for Loras
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+ lora:
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+ # Directory to look for LoRAs (default: loras).
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+ lora_dir: loras
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+
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+ # List of LoRAs to load and associated scaling factors (default scale: 1.0).
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+ # For the YAML file, add each entry as a YAML list:
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+ # - name: lora1
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+ # scaling: 1.0
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+ loras:
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+
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+ # Options for embedding models and loading.
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+ # NOTE: Embeddings requires the "extras" feature to be installed
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+ # Install it via "pip install .[extras]"
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+ embeddings:
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+ # Directory to look for embedding models (default: models).
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+ embedding_model_dir: models
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+
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+ # Device to load embedding models on (default: cpu).
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+ # Possible values: cpu, auto, cuda.
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+ # NOTE: It's recommended to load embedding models on the CPU.
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+ # If using an AMD GPU, set this value to 'cuda'.
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+ embeddings_device: cpu
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+
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+ # An initial embedding model to load on the infinity backend.
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+ embedding_model_name:
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+
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+ # Options for Sampling
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+ sampling:
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+ # Select a sampler override preset (default: None).
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+ # Find this in the sampler-overrides folder.
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+ # This overrides default fallbacks for sampler values that are passed to the API.
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+ override_preset:
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+
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+ # Options for development and experimentation
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+ developer:
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+ # Skip Exllamav2 version check (default: False).
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+ # WARNING: It's highly recommended to update your dependencies rather than enabling this flag.
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+ unsafe_launch: false
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+
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+ # Disable API request streaming (default: False).
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+ disable_request_streaming: false
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+
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+ # Enable the torch CUDA malloc backend (default: False).
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+ cuda_malloc_backend: false
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+
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+ # Run asyncio using Uvloop or Winloop which can improve performance.
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+ # NOTE: It's recommended to enable this, but if something breaks turn this off.
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+ uvloop: false
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+
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+ # Set process to use a higher priority.
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+ # For realtime process priority, run as administrator or sudo.
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+ # Otherwise, the priority will be set to high.
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+ realtime_process_priority: false