Transformer-MM-Explainability
by hila-chefer (personal account)
[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. (description from the project’s GitHub page)
Repository facts
- Stars
- 914
- Forks
- 118
- Open issues and pull requests
- 14
- Primary language
- Jupyter Notebook
- License
- MIT License (MIT)
- Owner
- hila-chefer · Personal account
- Created
- Mar 23, 2021
- Last push
- Aug 24, 2023
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