{ "type": "object", "properties": { "output": { "pretty_name": "Outputs", "type": "object", "properties": { "max_tokens": { "pretty_name": "Max Tokens", "type": "integer", "minimum": 16, "maximum": 4096, "step": 16, "default": 16, "description": "The maximum number of tokens to generate." }, "max_context_length": { "pretty_name": "Max Context Length", "type": "integer", "minimum": 128, "maximum": 999936, "step": 128, "default": 4096, "description": "The model's maximum context size." } }, "description": "Control the number of tokens to generate or the maximum context length." }, "sequence": { "pretty_name": "Sequence", "type": "object", "properties": { "n": { "pretty_name": "Number of Outputs", "type": "integer", "minimum": 1, "maximum": "20", "step": 1, "default": 1, "description": "The number of outputs to generate." }, "best_of": { "pretty_name": "Best of Outputs", "type": "integer", "minimum": 1, "maximum": "20", "step": 1, "default": 1, "description": "The number of outputs to generate and return the best of." } }, "description": "Control the number of outputs to generate." }, "penalties": { "pretty_name": "Penalties", "type": "object", "properties": { "presence_penalty": { "pretty_name": "Presence Penalty", "type": "float", "minimum": -2, "maximum": 2, "step": 0.001, "default": 0, "description": "Penalizes tokens based on their presence in the generated text." }, "frequency_penalty": { "pretty_name": "Frequency Penalty", "type": "float", "minimum": -2, "maximum": 2, "step": 0.001, "default": 0, "description": "Penalizes tokens based on their frequency in the generated text." }, "repetition_penalty": { "pretty_name": "Repetition Penalty", "type": "float", "minimum": 1, "maximum": 3, "step": 0.001, "default": 1, "description": "Penalizes tokens if they were generated in the previous text." } }, "description": "Penalize tokens based on their presence, frequency, and repetition in the generated text." }, "transform": { "pretty_name": "Transformations", "type": "object", "properties": { "temperature": { "pretty_name": "Temperature", "type": "float", "minimum": 0, "maximum": 10, "step": 0.001, "default": 1, "description": "Controls the randomness of the generated text." }, "dynatemp": { "pretty_name": "Dynamic Temperature", "type": "object", "properties": { "dynatemp_min": { "pretty_name": "Minimum Temperature", "type": "float", "minimum": 0, "maximum": 10, "step": 0.001, "default": 0, "description": "The minimum temperature value." }, "dynatemp_max": { "pretty_name": "Maximum Temperature", "type": "float", "minimum": 0, "maximum": 10, "step": 0.001, "default": 0, "description": "The maximum temperature value." }, "dynatemp_exponent": { "pretty_name": "Exponent", "type": "float", "minimum": 0.01, "maximum": 10, "step": 0.01, "default": 1, "description": "The exponent value for dynamic temperature." } }, "description": "Dynamically adjust temperature." }, "smoothing": { "pretty_name": "Smoothing", "type": "object", "properties": { "smoothing_factor": { "pretty_name": "Smoothing Factor", "type": "float", "minimum": 0, "maximum": 10, "step": 0.001, "default": 0, "description": "Apply a quadratic smoothing factor to the probability distribution." }, "smoothing_curve": { "pretty_name": "Smoothing Curve", "type": "float", "minimum": 1, "maximum": 10, "step": 0.001, "default": 1, "description": "Apply a cubic smoothing curve to the probability distribution." } }, "description": "Quadratic and Cubic Sampling methods." } }, "description": "Apply transformations to the probability distribution." }, "probabilistic": { "pretty_name": "Probabilistic", "type": "object", "properties": { "top_p": { "pretty_name": "Top P", "type": "float", "minimum": 0, "maximum": 1, "step": 0.001, "default": 1, "description": "The cumulative probability of the top tokens to keep." }, "top_a": { "pretty_name": "Top A", "type": "float", "minimum": 0, "maximum": 1, "step": 0.001, "default": 0, "description": "The threshold for the top tokens to keep." }, "min_p": { "pretty_name": "Min P", "type": "float", "minimum": 0, "maximum": 1, "step": 0.001, "default": 0, "description": "The minimum probability threshold of the tokens to keep." }, "top_k": { "pretty_name": "Top K", "type": "integer", "minimum": 0, "maximum": "1024", "step": 1, "default": 0, "description": "The number of top tokens to keep." }, "typical_p": { "pretty_name": "Typical P", "type": "float", "minimum": 0, "maximum": 1, "step": 0.001, "default": 1, "description": "Control the cumulative probability of tokens closest in surprise to the expected surprise to consider." }, "eta_cutoff": { "pretty_name": "Eta Cutoff", "type": "float", "minimum": 0, "maximum": 20, "step": 0.0001, "default": 0, "description": "The eta cutoff value." }, "epsilon_cutoff": { "pretty_name": "Epsilon Cutoff", "type": "float", "minimum": 0, "maximum": 9, "step": 0.0001, "default": 0, "description": "The epsilon cutoff value." }, "tfs": { "pretty_name": "Tail-Free Sampling", "type": "float", "minimum": 0, "maximum": 1, "step": 0.001, "default": 1, "description": "The cumulative curvature of the distribution to keep." } }, "description": "Control the probability distribution of the tokens." }, "mirostat": { "pretty_name": "Mirostat", "type": "object", "properties": { "mirostat_mode": { "pretty_name": "Mirostat Mode", "type": "integer", "minimum": 0, "maximum": 2, "step": 1, "default": 0, "description": "The mirostat mode to use. Only mode 2 is supported." }, "mirostat_tau": { "pretty_name": "Mirostat Tau", "type": "float", "minimum": 0, "maximum": 20, "step": 0.01, "default": 0, "description": "The target perplexity value that mirostat works towards." }, "mirostat_eta": { "pretty_name": "Mirostat Eta", "type": "float", "minimum": 0, "maximum": 1, "step": 0.001, "default": 0, "description": "The rate at which mirostat updates its internal surprisal" } }, "description": "An adaptive sampling method that directly controls the perplexity of the generated text." }, "beam_search": { "pretty_name": "Beam Search", "type": "object", "properties": { "use_beam_search": { "pretty_name": "Use Beam Search", "type": "bool", "default": false, "description": "Use beam search to generate the output." }, "length_penalty": { "pretty_name": "Length Penalty", "type": "float", "minimum": -5, "maximum": 5, "step": 0.1, "default": 1, "description": "The length penalty value." }, "early_stopping": { "pretty_name": "Early Stopping", "type": "bool", "default": false, "description": "Stop the beam search when at least `best_of` sentences are finished per batch." } }, "description": "Control the beam search parameters." }, "stops": { "pretty_name": "Stop Sequences", "type": "object", "properties": { "stop": { "pretty_name": "Stopping Strings", "type": "array", "items": { "type": "string" }, "default": [], "description": "The strings to stop the generation at." }, "stop_token_ids": { "pretty_name": "Stopping Token IDs", "type": "array", "items": { "type": "integer" }, "default": [], "description": "The token IDs to stop the generation at." }, "ignore_eos": { "pretty_name": "Ignore EOS", "type": "bool", "default": false, "description": "Ignore the End of Sequence token and continue generating." } }, "description": "Stop the generation at specific strings or token IDs." }, "logprobs": { "pretty_name": "Log Probabilities", "type": "object", "properties": { "logprobs": { "pretty_name": "Log probabilities", "type": "integer", "minimum": 0, "maximum": 10, "step": 1, "default": "null", "description": "The number of log probabilities to return for output tokens." }, "prompt_logprobs": { "pretty_name": "Prompt Log probabilities", "type": "integer", "minimum": 0, "maximum": 10, "step": 1, "default": "null", "description": "The number of log probabilities to return for prompt tokens." } }, "description": "Return log probabilities for tokens." }, "logit_processors": { "pretty_name": "Logits Processors", "type": "object", "properties": { "custom_token_bans": { "pretty_name": "Custom Token Bans", "type": "array", "items": { "type": "integer" }, "default": [], "description": "The token IDs to ban from being generated." }, "logit_bias": { "pretty_name": "Logit Bias", "type": "array", "items": { "type": "array", "items": { "type": "integer" }, "minItems": 2, "maxItems": 2 }, "default": [], "description": "The token ID and bias value to add to the logits." } }, "description": "Process the logits before generating the output." }, "misc": { "pretty_name": "Miscellaneous", "type": "object", "properties": { "seed": { "pretty_name": "Seed", "type": "integer", "minimum": "-inf", "maximum": "inf", "step": 1, "default": "null", "description": "The seed value for the random number generator." }, "skip_special_tokens": { "pretty_name": "Skip Special Tokens", "type": "bool", "default": true, "description": "Skip special tokens in the generated output." }, "spaces_between_special_tokens": { "pretty_name": "Spaces Between Special Tokens", "type": "bool", "default": true, "description": "Add spaces between special tokens in the generated output." }, "include_stop_str_in_output": { "pretty_name": "Include Stop String in Output", "type": "bool", "default": false, "description": "Include the stop string in the generated output." } }, "description": "Miscellaneous settings." } } }