langchain_experimental.llms.rellm_decoder.RELLM¶
class langchain_experimental.llms.rellm_decoder.RELLM[source]¶
Bases: HuggingFacePipeline
RELLM wrapped LLM using HuggingFace Pipeline API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param batch_size: int = 4¶
Batch size to use when passing multiple documents to generate.
param cache: Optional[bool] = None¶
param callback_manager: Optional[BaseCallbackManager] = None¶
param callbacks: Callbacks = None¶
param max_new_tokens: int = 200¶
Maximum number of new tokens to generate.
param metadata: Optional[Dict[str, Any]] = None¶
Metadata to add to the run trace.
param model_id: str = 'gpt2'¶
Model name to use.
param model_kwargs: Optional[dict] = None¶
Key word arguments passed to the model.
param pipeline_kwargs: Optional[dict] = None¶
Key word arguments passed to the pipeline.
param regex: RegexPattern [Required]¶
The structured format to complete.
param tags: Optional[List[str]] = None¶
Tags to add to the run trace.
param verbose: bool [Optional]¶
Whether to print out response text.
__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.