lmflow.pipeline.rm_inferencer#

Attributes#

logger

Classes#

RewardModelInferencer

Initializes the Inferencer class with given arguments.

Module Contents#

lmflow.pipeline.rm_inferencer.logger[source]#
class lmflow.pipeline.rm_inferencer.RewardModelInferencer(model_args: lmflow.args.ModelArguments, data_args: lmflow.args.DatasetArguments, inferencer_args: lmflow.args.InferencerArguments, **kwargs)[source]#

Bases: lmflow.pipeline.base_pipeline.BasePipeline

Initializes the Inferencer class with given arguments.

Parameters:

  • model_args (ModelArguments object.) – Contains the arguments required to load the model.

  • data_args (DatasetArguments object.) – Contains the arguments required to load the dataset.

  • inferencer_args (InferencerArguments object.) – Contains the arguments required to perform inference.

data_args[source]#
inferencer_args[source]#
model_args[source]#
local_rank[source]#
world_size[source]#
inference(model: lmflow.models.hf_text_regression_model.HFTextRegressionModel, dataset: lmflow.datasets.dataset.Dataset, transform_dataset_in_place: bool = True, use_vllm: bool = False, enable_distributed_inference: bool = False, **kwargs) → lmflow.datasets.dataset.Dataset[source]#
flatten_list(list_of_list: list[list]) → tuple[list, list[int]][source]#
compress_list(list_to_compress: list, sublist_lengths: list[int]) → list[list][source]#