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| # Copyright 2020-2025 The HuggingFace Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from dataclasses import dataclass, field | |
| from typing import Optional | |
| from datasets import load_dataset | |
| from huggingface_hub import ModelCard | |
| from transformers import HfArgumentParser | |
| class ScriptArguments: | |
| r""" | |
| Arguments for the script. | |
| Args: | |
| push_to_hub (`bool`, *optional*, defaults to `False`): | |
| Whether to push the dataset to the Hugging Face Hub. | |
| repo_id (`str`, *optional*, defaults to `"trl-lib/ultrafeedback-prompt"`): | |
| Hugging Face repository ID to push the dataset to. | |
| dataset_num_proc (`int` or `None`, *optional*, defaults to `None`): | |
| Number of workers to use for dataset processing. | |
| """ | |
| push_to_hub: bool = field( | |
| default=False, | |
| metadata={"help": "Whether to push the dataset to the Hugging Face Hub."}, | |
| ) | |
| repo_id: str = field( | |
| default="trl-lib/ultrafeedback-prompt", | |
| metadata={"help": "Hugging Face repository ID to push the dataset to."}, | |
| ) | |
| dataset_num_proc: Optional[int] = field( | |
| default=None, | |
| metadata={"help": "Number of workers to use for dataset processing."}, | |
| ) | |
| def to_unpaired_preference(example): | |
| prompt = [{"role": "user", "content": example["instruction"]}] | |
| return {"prompt": prompt} | |
| def drop_long_prompt(example): | |
| if len(example["prompt"][0]["content"]) > 512: | |
| return False | |
| else: | |
| return True | |
| model_card = ModelCard(""" | |
| --- | |
| tags: [trl] | |
| --- | |
| # UltraFeedback - Prompts Dataset | |
| ## Summary | |
| The UltraFeedback - Prompts dataset is a processed version of the [UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset for model evaluation on specific aspects like helpfulness, honesty, and instruction-following. | |
| ## Data Structure | |
| - **Format**: [Conversational](https://huggingface.co/docs/trl/main/dataset_formats#conversational) | |
| - **Type**: [Prompt-only](https://huggingface.co/docs/trl/main/dataset_formats#prompt-only) | |
| Column: | |
| - `"prompt"`: The input question or instruction provided to the model. | |
| ## Generation script | |
| The script used to generate this dataset can be found [here](https://github.com/huggingface/trl/blob/main/examples/datasets/ultrafeedback-prompt.py). | |
| """) | |
| if __name__ == "__main__": | |
| parser = HfArgumentParser(ScriptArguments) | |
| script_args = parser.parse_args_into_dataclasses()[0] | |
| dataset = load_dataset("openbmb/UltraFeedback", split="train") | |
| dataset = dataset.map( | |
| to_unpaired_preference, | |
| remove_columns=["source", "instruction", "models", "completions", "correct_answers", "incorrect_answers"], | |
| num_proc=script_args.dataset_num_proc, | |
| ) | |
| dataset = dataset.filter(drop_long_prompt) | |
| dataset = dataset.train_test_split(test_size=0.05, seed=42) | |
| if script_args.push_to_hub: | |
| dataset.push_to_hub(script_args.repo_id) | |
| model_card.push_to_hub(script_args.repo_id, repo_type="dataset") | |