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--- |
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dataset_info: |
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features: |
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- name: index |
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dtype: int64 |
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- name: prompt |
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dtype: string |
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- name: name |
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dtype: string |
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- name: story |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 656176355 |
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num_examples: 66851 |
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download_size: 370967759 |
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dataset_size: 656176355 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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This is a medium-length story dataset introduced in **LongStory: Coherent, Complete and Length Controlled Long story Generation** : [https://arxiv.org/abs/2311.15208](https://arxiv.org/abs/2311.15208). |
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The dataset was collected by the authors from Reedsy Prompts : [https://blog.reedsy.com/short-stories/](https://blog.reedsy.com/short-stories/), as of May 2023. |
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In the original paper, the authors use a 60k/4k/4k train/validation/test split. |
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For comparison: |
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- **WritingPrompts** (Fan et al., 2018): ~768 tokens per story |
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- **Booksum** (Kryściński et al., 2021): ~6,065 tokens per story |
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- **BookCorpus** (Project Gutenberg): ~90,000 words per story (approx.) |
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- (ours) **ReedsyPrompts** : ~2426 tokens per story |
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Use this : |
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<pre><code> |
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from datasets import load_dataset |
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ds = load_dataset("Iyan/reedsyPrompts") |
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print(ds["train"][0]['index']) |
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print(ds["train"][0]['prompt']) # the prompt of the story |
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print(ds["train"][0]['name']) # the title of the story |
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print(ds["train"][0]['story']) |
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</code></pre> |
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