--- size_categories: n<1K dataset_info: features: - name: prompt dtype: 'null' - name: model_name dtype: 'null' - name: generation dtype: 'null' - name: completion dtype: 'null' splits: - name: train num_bytes: 0 num_examples: 10 download_size: 1780 dataset_size: 0 configs: - config_name: default data_files: - split: train path: data/train-* tags: - synthetic - distilabel - rlaif - datacraft ---

Built with Distilabel

# Dataset Card for my-distiset This dataset has been created with [distilabel](https://distilabel.argilla.io/). The pipeline script was uploaded to easily reproduce the dataset: [app.py](https://huggingface.co/datasets/JeCabrera/my-distiset/raw/main/app.py). It can be run directly using the CLI: ```console distilabel pipeline run --script "https://huggingface.co/datasets/JeCabrera/my-distiset/raw/main/app.py" ``` ## Dataset Summary This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI: ```console distilabel pipeline run --config "https://huggingface.co/datasets/JeCabrera/my-distiset/raw/main/pipeline.yaml" ``` or explore the configuration: ```console distilabel pipeline info --config "https://huggingface.co/datasets/JeCabrera/my-distiset/raw/main/pipeline.yaml" ``` ## Dataset structure The examples have the following structure per configuration:
Configuration: default
```json { "completion": null, "generation": null, "model_name": null, "prompt": null } ``` This subset can be loaded as: ```python from datasets import load_dataset ds = load_dataset("JeCabrera/my-distiset", "default") ``` Or simply as it follows, since there's only one configuration and is named `default`: ```python from datasets import load_dataset ds = load_dataset("JeCabrera/my-distiset") ```
## References ``` @misc{xu2024magpiealignmentdatasynthesis, title={Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing}, author={Zhangchen Xu and Fengqing Jiang and Luyao Niu and Yuntian Deng and Radha Poovendran and Yejin Choi and Bill Yuchen Lin}, year={2024}, eprint={2406.08464}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2406.08464}, } ```