REPOGEO REPORT · LITE
jessevig/bertviz
Default branch master · commit 79dbaebf · scanned 5/15/2026, 1:16:58 PM
GitHub: 8,061 stars · 877 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface jessevig/bertviz, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highhomepage#1Add a homepage link to the Colab tutorial
Why:
COPY-PASTE FIXhttps://colab.research.google.com/drive/1hXIQ77A4TYS4y3UthWF-Ci7V7vVUoxmQ?usp=sharing
- mediumtopics#2Add more specific topics related to attention visualization and interpretability
Why:
CURRENTbert, gpt2, machine-learning, natural-language-processing, neural-network, nlp, pytorch, roberta, transformer, transformers, visualization
COPY-PASTE FIXbert, gpt2, machine-learning, natural-language-processing, neural-network, nlp, pytorch, roberta, transformer, transformers, visualization, attention-visualization, attention-mechanism, deep-learning-interpretability
- lowreadme#3Refine the README's opening sentence to explicitly mention inspecting attention heads across layers
Why:
CURRENTBertViz is an interactive tool for visualizing attention in Transformer language models. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models.
COPY-PASTE FIXBertViz is an interactive tool for visualizing and inspecting attention heads across layers in Transformer language models. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Hugging Face Transformers library · recommended 2×
- TensorBoard · recommended 2×
- Captum · recommended 2×
- LIME · recommended 2×
- Matplotlib · recommended 1×
- CATEGORY QUERYHow to visualize attention patterns in transformer models for better interpretability?you: #4AI recommended (in order):
- Hugging Face Transformers library
- Matplotlib
- Seaborn
- BertViz (jessevig/bertviz) ← you
- ExBERT
- TensorBoard
- Captum
- LIME
- SHAP
Show full AI answer
- CATEGORY QUERYInteractive tool to inspect attention heads across layers in deep learning models?you: not recommendedAI recommended (in order):
- exBERT
- LIME
- Captum
- TensorBoard
- Hugging Face Transformers library
AI recommended 5 alternatives but never named jessevig/bertviz. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of jessevig/bertviz?passAI named jessevig/bertviz explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts jessevig/bertviz in production, what risks or prerequisites should they evaluate first?passAI named jessevig/bertviz explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo jessevig/bertviz solve, and who is the primary audience?passAI named jessevig/bertviz explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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jessevig/bertviz — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite