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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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+
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+ # scientific_lay_summarisation - elife - normalized
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+
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+
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+
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+ ## Contents
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+
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+ loadwith datasets:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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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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+
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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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+ ```