# hila-chefer/transformer-mm-explainability

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908 stars · 116 forks · Jupyter Notebook · MIT

## Links

- GitHub: https://github.com/hila-chefer/Transformer-MM-Explainability
- awesome-repositories: https://awesome-repositories.com/repository/hila-chefer-transformer-mm-explainability.md

## Topics

`clip` `detr` `explainability` `explainable-ai` `interpretability` `lxmert` `transformer` `transformers` `visualbert` `visualization` `vqa`

## Description

[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

## Tags

### Part of an Awesome List

- [Representation Learning](https://awesome-repositories.com/f/awesome-lists/ai/representation-learning.md) — Explainability for bi-modal and encoder-decoder transformers.