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CrynuxConfig

class CrynuxConfig(BaseConfig):
Defines the parameters for generating chat completions using the OpenAI API. Parameters:
  • temperature (float, optional): Sampling temperature to use, between :obj:0 and :obj:2. Higher values make the output more random, while lower values make it more focused and deterministic. (default: :obj:None)
  • top_p (float, optional): An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So :obj:0.1 means only the tokens comprising the top 10% probability mass are considered. (default: :obj:None)
  • n (int, optional): How many chat completion choices to generate for each input message. (default: :obj:None)
  • response_format (object, optional): An object specifying the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106. Setting to {"type": "json_object"} enables JSON mode, which guarantees the message the model generates is valid JSON. Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly “stuck” request. Also note that the message content may be partially cut off if finish_reason=“length”, which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.
  • stream (bool, optional): If True, partial message deltas will be sent as data-only server-sent events as they become available. (default: :obj:None)
  • stop (str or list, optional): Up to :obj:4 sequences where the API will stop generating further tokens. (default: :obj:None)
  • max_tokens (int, optional): The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model’s context length. (default: :obj:None)
  • presence_penalty (float, optional): Number between :obj:-2.0 and :obj:2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics. See more information about frequency and presence penalties. (default: :obj:None)
  • frequency_penalty (float, optional): Number between :obj:-2.0 and :obj:2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim. See more information about frequency and presence penalties. (default: :obj:None)
  • logit_bias (dict, optional): Modify the likelihood of specified tokens appearing in the completion. Accepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from :obj:-100 to :obj:100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between:obj: -1
  • and: obj:1 should decrease or increase likelihood of selection; values like :obj:-100 or :obj:100 should result in a ban or exclusive selection of the relevant token. (default: :obj:None)