| --- |
| dataset_info: |
| features: |
| - name: messages |
| list: |
| - name: content |
| dtype: string |
| - name: role |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 902953 |
| num_examples: 2446 |
| download_size: 246445 |
| dataset_size: 902953 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| task_categories: |
| - text-generation |
| - text2text-generation |
| - question-answering |
| language: |
| - en |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
|
|
| ## Description |
|
|
| The dataset is from [medalpaca/medical_meadow_pubmed_causal](https://huggingface.co/datasets/medalpaca/medical_meadow_pubmed_causal), formatted as dialogues for speed and ease of use. Many thanks to author for releasing it. |
| Importantly, this format is easy to use via the default chat template of `transformers`, meaning you can use [huggingface/alignment-handbook](https://github.com/huggingface/alignment-handbook) immediately, [unsloth](https://github.com/unslothai/unsloth). |
|
|
| ## Structure |
|
|
| *View online through viewer.* |
|
|
| ## Note |
|
|
| We advise you to reconsider before use, thank you. If you find it useful, please like and follow this account. |
|
|
| ## Reference |
|
|
| The **Ghost X** was developed with the goal of researching and developing artificial intelligence useful to humans. |
|
|
| - HuggingFace: [ghost-x](https://huggingface.co/ghost-x) |
| - Github: [ghost-x-ai](https://github.com/ghost-x-ai) |
| - X / Twitter: [ghostx_ai](https://twitter.com/ghostx_ai) |
| - Website: [ghost-x.org](https://ghost-x.org/) |
|
|
| ## Citation |
|
|
| ```json |
| @inproceedings{yu-etal-2019-detecting, |
| title = "Detecting Causal Language Use in Science Findings", |
| author = "Yu, Bei and |
| Li, Yingya and |
| Wang, Jun", |
| booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)", |
| month = nov, |
| year = "2019", |
| address = "Hong Kong, China", |
| publisher = "Association for Computational Linguistics", |
| url = "https://aclanthology.org/D19-1473", |
| doi = "10.18653/v1/D19-1473", |
| pages = "4664--4674", |
| } |
| ``` |
|
|
| ### ~ |
