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codeKgu committed Nov 17, 2020
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# Multimodal Transformers | Transformers with Tabular Data

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**[Documentation](https://multimodal-toolkit.readthedocs.io/en/latest/index.html)** | **[Colab Notebook](https://multimodal-toolkit.readthedocs.io/en/latest/notes/colab_example.html)**
**[Documentation](https://multimodal-toolkit.readthedocs.io/en/latest/index.html)** | **[Colab Notebook](https://multimodal-toolkit.readthedocs.io/en/latest/notes/colab_example.html)** | **[Blog Post](https://medium.com/georgian-impact-blog/how-to-incorporate-tabular-data-with-huggingface-transformers-b70ac45fcfb4)**

A toolkit for incorporating multimodal data on top of text data for classification
and regression tasks. It uses HuggingFace transformers as the base model for text features.
The toolkit adds a combining module that takes the outputs of the transformer in addition to categorical and numerical features
to produce rich multimodal features for downstream classification/regression layers.
Given a pretrained transformer, the parameters of the combining module and transformer are trained based
on the supervised task.
on the supervised task. For a brief literature review, check out the accompanying [blog post](https://medium.com/georgian-impact-blog/how-to-incorporate-tabular-data-with-huggingface-transformers-b70ac45fcfb4) on Georgian's Impact Blog.

![](https://drive.google.com/uc?export=view&id=1aMNrv5kHDcaq8gS1EFtA6Ri4Tg_aff4E)



## Installation
The code was developed in Python 3.7 with PyTorch and Transformer 3.0.
The code was developed in Python 3.7 with PyTorch and transformers 3.1.
The multimodal specific code is in `multimodal_transformers` folder.
```
pip install multimodal-transformers
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