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A flexible PyTorch-based framework for sentiment analysis tasks, easily adaptable to diverse text datasets. This project streamlines and modernizes sentiment analysis methods with PyTorch.

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Jack-Development/Text2Sentiment

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Text2Sentiment

Text2Sentiment is a flexible, reusable framework for building Text Classification models. This repository is specifically designed for PyTorch and can be applied to numerous different datasets.

Inspired by bentrevett's PyTorch Sentiment Analysis and the PyTorch Documentation Examples, this project was created to modernize older resources and replace the usage of legacy packages.

The initial implementation performs Sentiment Analysis on the TorchText IMDB dataset, but the architecture of the codebase allows for easy adaptation to other text datasets.

Skills and Technologies Used

The project heavily relies on:

  • Python
  • PyTorch
  • Ubuntu
python pytorch ubuntu

Getting Started

Coming soon...

A detailed guide on how to use this project will be published shortly. The guide will contain information about how to adapt the codebase to work with various text datasets.

Contributing

Contributions, issues and feature requests are welcome. Feel free to check issues page if you want to contribute.

License

This project is MIT licensed.

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A flexible PyTorch-based framework for sentiment analysis tasks, easily adaptable to diverse text datasets. This project streamlines and modernizes sentiment analysis methods with PyTorch.

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