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README.md
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---
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license: mit
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---
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---
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license: mit
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task_categories:
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- summarization
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- text2text-generation
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language:
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- en
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size_categories:
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- 10K<n<100K
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source_datasets: tomasg25/scientific_lay_summarisation
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---
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# scientific_lay_summarisation - elife - normalized
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## Contents
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loadwith datasets:
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```python
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from datasets import load_dataset
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# If the dataset is gated/private, make sure you have run huggingface-cli login
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dataset = load_dataset("pszemraj/scientific_lay_summarisation-elife-norm")
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dataset
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```
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Output:
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```python
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DatasetDict({
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train: Dataset({
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features: ['article', 'summary', 'section_headings', 'keywords', 'year', 'title', 'article_length', 'summary_length'],
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num_rows: 4346
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})
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test: Dataset({
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features: ['article', 'summary', 'section_headings', 'keywords', 'year', 'title', 'article_length', 'summary_length'],
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num_rows: 241
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})
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validation: Dataset({
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features: ['article', 'summary', 'section_headings', 'keywords', 'year', 'title', 'article_length', 'summary_length'],
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num_rows: 241
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})
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})
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```
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