{"adoption": {"forks": 261, "observed_at": "2026-08-28T04:06:05.377403+00:00", "stars": 2014}, "canonical_url": "https://ross.abutalabs.com/products/transformer-explainability", "card": {"archived": false, "artifact_type": "library", "description": "[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.", "domain": ["deep-learning", "computer-vision", "artificial-intelligence"], "enriched": true, "function": ["machine-learning", "nlp", "image-processing", "data-visualization"], "health_score": 20, "homepage": null, "language": "Jupyter Notebook", "license": "MIT", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["hila-chefer/Transformer-Explainability"], "name": "hila-chefer/Transformer-Explainability", "platform": ["python"], "pushed_at": "2024-01-24T05:59:39+00:00", "repo": "hila-chefer/Transformer-Explainability", "stars": 2014, "tags": ["explainability", "vision-transformer", "bert", "attention-visualization", "interpretability", "cvpr-2021", "pytorch", "research-code", "natural-language-processing"], "topics": ["deep-learning", "vision-transformer", "bert-model", "bert", "explainability", "transformer-interpretability", "perturbation", "attention-visualization", "visualize-classifications", "vit", "attention-matrix", "cvpr2021"], "urls": [], "use_cases": ["visualize which image patches a ViT used for its classification", "explain BERT token classifications with relevance heatmaps", "generate per-class explanations for transformer predictions", "understand transformer attention beyond raw attention maps", "reproduce CVPR 2021 transformer interpretability research", "add explainability to DeiT or other vision transformers"], "what_it_is": "Official PyTorch implementation of the CVPR 2021 paper 'Transformer Interpretability Beyond Attention Visualization', providing relevance-based explanations for classifications made by Transformer models like ViT and BERT. It ships as Jupyter/Colab notebooks demonstrating per-class explanation visualization for vision and NLP tasks.", "when_to_avoid": ["you need a production-ready, maintained explainability library with broad model support", "you need explainability for non-PyTorch or multimodal/encoder-decoder transformers (see the authors' follow-up work)", "you need an actively developed tool - the repo is primarily a paper artifact"], "when_to_choose": ["you need research-grade relevance/saliency explanations for ViT or BERT models", "you want per-class visual explanations rather than plain attention visualization", "you want runnable Colab notebooks to experiment quickly"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/transformer-explainability", "repo": "hila-chefer/Transformer-Explainability", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:06:05.377403+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T03:00:49.509666+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "47d40facad62030f48fa1d213e107d935f24db2fe8a61fd8451df0df0a4eac19", "fetched_at": "2026-08-28T04:06:05.377403+00:00", "kind": "readme", "missing": false, "url": "https://github.com/hila-chefer/Transformer-Explainability"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 2109, "days_push": 952, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}