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--- |
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license: apache-2.0 |
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task_categories: |
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- text-generation |
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- text2text-generation |
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language: |
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- en |
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tags: |
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- keyword-generation |
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- Science |
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- Research |
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- Academia |
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- Innovation |
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- Technology |
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pretty_name: scientific papers with their author keywords |
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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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dataset_info: |
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features: |
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- name: title |
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dtype: string |
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- name: abstract |
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dtype: string |
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- name: keywords |
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dtype: string |
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- name: source_name |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 2771926367 |
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num_examples: 2640662 |
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download_size: 1603171250 |
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dataset_size: 2771926367 |
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--- |
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# SciDocs Keywords exKEYliWORD |
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## Dataset Description |
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`SciDocs2Keywords` is a dataset consisting of scientific papers (title and abstract) and their associated author-provided keywords. It is designed for use in task of keyword extraction or abstraction. |
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Each entry in the dataset includes: |
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- Title: The title of the scientific paper. |
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- Abstract: A brief summary of the paper. |
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- Author Keywords: Keywords provided by the authors to highlight the main topics or concepts of the paper. |
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- Source: Paper provider source API. |
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## Associated Model |
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soon... |
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## How to Use |
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To use this dataset for model training or evaluation, you can load it using the Hugging Face `datasets` library as follows: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("nicolauduran45/scidocs-keywords-exkeyliword") |
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print(dataset[0]) |
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``` |
