ratransformers 0.1.0

RATransformer - make a transformer model learn implicit relations passed in the input

RATransformers 🐭

RATransformers, short for Relation-Aware Transformers, is a package built on top of transformers 🤗 that enables the training/fine-tuning of models with extra relation-aware input features.

Example - Encoding a table in TableQA (Question Answering on Tabular Data)

[Notebook Link]

In this example we can see that passing the table as text with no additional information to the model is a poor representation.

With RATransformers 🐭 you are to able to encode the table in a more structured way by passing specific relations within the input. RATransformers 🐭 also allows you to pass further features related with each input word/token.

Check more examples in [here]

Installation

Install directly from PyPI:

pip install ratransformers

Supported Models

Currently we support a limited number of transformer models:

• BART
• BERT
• GPT-2
• RoBERTa
• T5

Want another model? Feel free to open an Issue or create a Pull Request and let's get started 🚀