RRepoGEO

REPOGEO REPORT · LITE

poloclub/transformer-explainer

Default branch main · commit bfe50afb · scanned 6/27/2026, 9:21:50 PM

GitHub: 7,916 stars · 868 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

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 poloclub/transformer-explainer, 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.

OVERALL DIRECTION
  • highreadme#1
    Reposition README's opening paragraph to emphasize unique interactive learning differentiator

    Why:

    CURRENT
    Transformer Explainer is an interactive visualization tool designed to help anyone learn how Transformer-based models like GPT work. It runs a live GPT-2 model right in your browser, allowing you to experiment with your own text and observe in real time how internal components and operations of the Transformer work together to predict the next tokens.
    COPY-PASTE FIX
    Transformer Explainer is an interactive visualization tool designed to help anyone visually learn and experiment with the *entire internal computation and information flow* within Transformer-based models like GPT. It provides a holistic, step-by-step visualization, going beyond just attention mechanisms, to illustrate how tokens are processed through various layers. Running a live GPT-2 model in your browser, it allows you to observe in real time how internal components and operations work together to predict the next tokens.
  • mediumtopics#2
    Add more specific topics related to interactive learning and model explanation

    Why:

    CURRENT
    deep-learning, generative-ai, gpt, langauge-model, llm, visualization
    COPY-PASTE FIX
    deep-learning, generative-ai, gpt, langauge-model, llm, visualization, interactive-learning, transformer-architecture, model-explanation
  • lowreadme#3
    Add a 'Who is this for?' section to clarify audience and purpose

    Why:

    COPY-PASTE FIX
    ## Who is this for?
Transformer Explainer is ideal for students, educators, and researchers who want to gain a deeper, intuitive understanding of how large language models work at a fundamental level. It serves as an educational tool rather than a production monitoring or debugging system.

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.

Recall
0 / 2
0% of queries surface poloclub/transformer-explainer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Neuroscope
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Neuroscope · recommended 2×
  2. LIME · recommended 2×
  3. SHAP · recommended 2×
  4. LlamaIndex · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    How can I visually understand the internal workings of large language models?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. LangSmith
    4. TransformerLens
    5. Neuroscope
    6. Ecco
    7. Interpret-LM
    8. Hugging Face Transformers
    9. Gradio
    10. Streamlit
    11. captum
    12. LIME
    13. SHAP

    AI recommended 13 alternatives but never named poloclub/transformer-explainer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What interactive tools help visualize and experiment with transformer model components in real-time?
    you: not recommended
    AI recommended (in order):
    1. TensorBoard
    2. exBERT
    3. LIME
    4. SHAP
    5. AttentionViz
    6. Hugging Face Transformers library
    7. Matplotlib
    8. Seaborn
    9. Neuroscope

    AI recommended 9 alternatives but never named poloclub/transformer-explainer. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

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 poloclub/transformer-explainer?
    pass
    AI did not name poloclub/transformer-explainer — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts poloclub/transformer-explainer in production, what risks or prerequisites should they evaluate first?
    pass
    AI named poloclub/transformer-explainer 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 poloclub/transformer-explainer solve, and who is the primary audience?
    pass
    AI named poloclub/transformer-explainer explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite