hh_rlhf_helpful_dataset

torchtune.datasets.hh_rlhf_helpful_dataset(tokenizer: ModelTokenizer, *, source: str = 'RLHFlow/HH-RLHF-Helpful-standard', column_map: Optional[Dict[str, str]] = None, train_on_input: bool = False, new_system_prompt: Optional[str] = None, split: str = 'train', **load_dataset_kwargs: Dict[str, Any]) → PreferenceDataset

Constructs preference datasets similar to Anthropic’s helpful/harmless RLHF data. This is the processed helpful subset of the original dataset in a standardized format.

Parameters:

• tokenizer (ModelTokenizer) – Tokenizer used by the model that implements the tokenize_messages method.

• source (str) – path to dataset repository on Hugging Face. For local datasets, define source as the data file type (e.g. “json”, “csv”, “text”) and pass in the filepath in data_files. See Hugging Face’s load_dataset (https://huggingface.co/docs/datasets/en/package_reference/loading_methods#datasets.load_dataset.path) for more details. Default is RLHFlow/HH-RLHF-Helpful-standard.

• column_map (Optional[Dict[str, str]]) – a mapping from the expected columns “chosen” and “rejected” in the message transform ChosenRejectedToMessages to the new column names in the dataset. Keys should be “chosen” and “rejected” and values should be the actual column names. If None, keep the default columns “chosen” and “rejected”.

• train_on_input (bool) – Whether the model is trained on the prompt or not. Default is False.

• new_system_prompt (Optional[str]) – if specified, prepend a system message to every sample for both chosen and rejected. This can serve as instructions to guide the model response. Setting this will OVERRIDE any system messages already present in the dataset. Default is None.

• split (str) – split argument for datasets.load_dataset. You can use this argument to load a subset of a given split, e.g. split="train[:10%]". Default is “train”.

• **load_dataset_kwargs (Dict[str, Any]) – additional keyword arguments to pass to load_dataset.

Returns:

The preference dataset built from source paired data.

Return type:

PreferenceDataset