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README.md

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----
-language:
-- en
-license:
-- mit
-multilinguality:
-- monolingual
-pretty_name: AESLC - Cleaned & Keyword Extracted
-source_datasets:
-- aeslc
-tags:
-- text2text generation
-- email
-- email generation
-- enron
----
-
-## about
-
-- aeslc dataset but cleaned and keywords extracted to a new column
-- an EDA website generated via pandas profiling [is on netlify here](https://aeslc-kw-train-eda.netlify.app/)
-
-```
-DatasetDict({
-    train: Dataset({
-        features: ['email_body', 'subject_line', 'clean_email', 'clean_email_keywords'],
-        num_rows: 14436
-    })
-    test: Dataset({
-        features: ['email_body', 'subject_line', 'clean_email', 'clean_email_keywords'],
-        num_rows: 1906
-    })
-    validation: Dataset({
-        features: ['email_body', 'subject_line', 'clean_email', 'clean_email_keywords'],
-        num_rows: 1960
-    })
-})
-```
-
-## Python usage
-
-
-Basic example notebook [here](https://colab.research.google.com/gist/pszemraj/18742da8db4a99e57e95824eaead285a/scratchpad.ipynb).
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset("postbot/aeslc_kw")
-```
-
-## Citation
-
-```
-@InProceedings{zhang2019slg,
-  author =      "Rui Zhang and Joel Tetreault",
-  title =       "This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation",
-  booktitle =   "Proceedings of The 57th Annual Meeting of the Association for Computational Linguistics",
-  year =        "2019",
-  address =     "Florence, Italy"
-}
-```

train.csv → postbot--aeslc_kw/csv-test.parquet

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