# hila-chefer/Transformer-Explainability

<https://repo.masters-masters.com/repos/hila-chefer/Transformer-Explainability>

[Accueil](https://repo.masters-masters.com/) › [hila-chefer](https://repo.masters-masters.com/owners/hila-chefer) › [Transformer-Explainability](https://repo.masters-masters.com/repos/hila-chefer/Transformer-Explainability)

hila-chefer/Transformer-Explainability, dépôt open source à 2 021 étoiles sur GitHub. Carte RC de RepoMasters. \[CVPR 2021\] Official PyTorch implementation for…

| Champ | Valeur |
| --- | --- |
| Propriétaire | [hila-chefer](https://repo.masters-masters.com/owners/hila-chefer) |
| Étoiles | 2 021 |
| Forks | 260 |
| Langage | [Jupyter Notebook](https://repo.masters-masters.com/languages/jupyter-notebook) |
| Licence | MIT |
| Création | 2020 |
| Sujets | deep-learning, vision-transformer, bert-model, bert, explainability, transformer-interpretability, perturbation, attention-visualization, visualize-classifications, vit |
| Rang | [RC (2 000 à 4 999 ★)](https://repo.masters-masters.com/ranks/blockbuster) |
| Voir sur GitHub | [hila-chefer/Transformer-Explainability](https://github.com/hila-chefer/Transformer-Explainability) |

## Fiche du dépôt

\[CVPR 2021\] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

Rang des dépôts qui ont 2 000 à 4 999 ★ sur GitHub. Probabilité publiée par carte tirée : 3 %. Rareté : Épique.

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Données : GitHub · Illustration : image publique du projet, pixelisée par RepoMasters.
