Transformer-MM-Explainability
[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.
How to download and setup Transformer-MM-Explainability
Open terminal and run command
git clone https://github.com/hila-chefer/Transformer-MM-Explainability.git
git clone is used to create a copy or clone of Transformer-MM-Explainability repositories.
You pass git clone a repository URL. it supports a few different network protocols and corresponding URL formats.
Also you may download zip file with Transformer-MM-Explainability https://github.com/hila-chefer/Transformer-MM-Explainability/archive/master.zip
Or simply clone Transformer-MM-Explainability with SSH
[email protected]:hila-chefer/Transformer-MM-Explainability.git
If you have some problems with Transformer-MM-Explainability
You may open issue on Transformer-MM-Explainability support forum (system) here: https://github.com/hila-chefer/Transformer-MM-Explainability/issuesSimilar to Transformer-MM-Explainability repositories
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