field n_parts: int = -1#
Number of parts to split the model into.
If -1, the number of parts is automatically determined.
field n_threads: Optional[int] = None#
Number of threads to use.
If None, the number of threads is automatically determined.
field repeat_penalty: Optional[float] = 1.1#
The penalty to apply to repeated tokens.
field seed: int = -1#
Seed. If -1, a random seed is used.
field stop: Optional[List[str]] = []#
A list of strings to stop generation when encountered.
field streaming: bool = True#
Whether to stream the results, token by token.
field suffix: Optional[str] = None#
A suffix to append to the generated text. If None, no suffix is appended.
field tags: Optional[List[str]] = None#
Tags to add to the run trace.
field temperature: Optional[float] = 0.8#
The temperature to use for sampling.
field top_k: Optional[int] = 40#
The top-k value to use for sampling.
field top_p: Optional[float] = 0.95#
The top-p value to use for sampling.
field use_mlock: bool = False#
Force system to keep model in RAM.
field use_mmap: Optional[bool] = True#
Whether to keep the model loaded in RAM
field verbose: bool [Optional]#
Whether to print out response text.
field vocab_only: bool = False#
Only load the vocabulary, no weights.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[langchain.callbacks.base.BaseCallbackHandler], langchain.callbacks.base.BaseCallbackManager]] = None, **kwargs: Any) → str#
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/llms.html