param n_parts: int = -1¶
Number of parts to split the model into.
If -1, the number of parts is automatically determined.
param n_predict: Optional[int] = 256¶
The maximum number of tokens to generate.
param n_threads: Optional[int] = 4¶
Number of threads to use.
param repeat_last_n: Optional[int] = 64¶
Last n tokens to penalize
param repeat_penalty: Optional[float] = 1.18¶
The penalty to apply to repeated tokens.
param seed: int = 0¶
Seed. If -1, a random seed is used.
param stop: Optional[List[str]] = []¶
A list of strings to stop generation when encountered.
param streaming: bool = False¶
Whether to stream the results or not.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param temp: Optional[float] = 0.7¶
The temperature to use for sampling.
param top_k: Optional[int] = 40¶
The top-k value to use for sampling.
param top_p: Optional[float] = 0.1¶
The top-p value to use for sampling.
param use_mlock: bool = False¶
Force system to keep model in RAM.
param verbose: bool [Optional]¶
Whether to print out response text.
param vocab_only: bool = False¶
Only load the vocabulary, no weights.
__call__(prompt: str, stop: Optional[List[str]] = None, callbacks: Optional[Union[List[BaseCallbackHandler], BaseCallbackManager]] = None, *, tags: Optional[List[str]] = None, metadata: Optional[Dict[str, Any]] = None, **kwargs: Any) → str¶
Check Cache and run the LLM on the given prompt and input.