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hila-chefer/Transformer-Explainability
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
2.0k 259 +1/wk
GitHub
attention-matrix attention-visualization bert bert-model cvpr2021 deep-learning explainability perturbation transformer-interpretability vision-transformer visualize-classifications vit
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hila-chefer/Transformer-Explainability has +1 stars this period . 7-day velocity: 0.1%.
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| Metric | Transformer-Explainability | make-a-video-pytorch | RecLearn | Advanced-Deep-Learning-with-Keras |
|---|---|---|---|---|
| Stars | 2.0k | 2.0k | 2.0k | 2.0k |
| Forks | 259 | 185 | 497 | 1.0k |
| Weekly Growth | +1 | +0 | +0 | +0 |
| Language | Jupyter Notebook | Python | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | MIT | MIT | MIT |
Capability Radar vs make-a-video-pytorch
Transformer-Explainability
make-a-video-pytorch
Maintenance Activity 0
Last code push 806 days ago.
Community Engagement 65
Fork-to-star ratio: 13.0%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 43
+1 stars this period — 0.05% growth rate.
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.