NLP-with-transformers

This repository is used to show the algorithms from the book Natural Language Processing with Transformers, these algorithms were presented in the classroom of the Database Topics III class of the Department of Informatics at PUC-Rio presented by the teachers Marco A. Casanova and Antonio L. Furtado.

What is?

This is an adapted version of the algorithms presented in book Natural Language Processing with Transformers by the authors Lewis Tunstall, Leandro von Werra & Thomas Wolf.

To learn more about the content, consider using the book with the authors own annotations.

Summary

2. Text Classification
   • One-hot Vectors
   • Text Classification with Tensorflow

References

• Natural Language Processing with Transformers

  Tunstall, Lewis, Leandro Von Werra, and Thomas Wolf. Natural language processing with transformers. " O'Reilly Media, Inc.", 2022.

• CARER: Contextualized Affect Representations for Emotion Recognition

  Saravia, Elvis, et al. "Carer: Contextualized affect representations for emotion recognition." Proceedings of the 2018 conference on empirical methods in natural language processing. 2018.

• DistilBERT base uncased distilled SQuAD

  Sanh, Victor, et al. "DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter." arXiv preprint arXiv:1910.01108 (2019).

• Umap: Uniform manifold approximation and projection for dimension reduction

  McInnes, Leland, John Healy, and James Melville. "Umap: Uniform manifold approximation and projection for dimension reduction." arXiv preprint arXiv:1802.03426 (2018).

Issues

Feel free to submit issues and enhancement requests.

Contribution

1. Fork the project
2. Create a branch for your modification (git checkout -b my-new-resource)
3. Do the commit (git commit -am 'Adding a new resource...')
4. Push (git push origin my-new-resource)
5. Create a new Pull Request