RRepoGEO

REPOGEO REPORT · LITE

abacaj/awesome-transformers

Default branch main · commit d3b1b533 · scanned 6/14/2026, 4:38:17 AM

GitHub: 683 stars · 50 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 abacaj/awesome-transformers, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    awesome-list, transformers, llm, nlp, deep-learning, machine-learning, ai-models, model-comparison, curated-list
  • highreadme#2
    Strengthen README opening to emphasize "awesome list" and "comparison resource"

    Why:

    CURRENT
    # Awesome Transformers

A curated list of awesome transformer models.
    COPY-PASTE FIX
    # Awesome Transformers: A Curated Resource List

This is an awesome list providing a comprehensive, curated collection of transformer models, their papers, sources, and licenses. It serves as a central resource for comparing different architectures and finding the right model for your needs.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/abacaj/awesome-transformers

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 abacaj/awesome-transformers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
BERT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. BERT · recommended 1×
  2. RoBERTa · recommended 1×
  3. GPT-3 / GPT-4 · recommended 1×
  4. T5 · recommended 1×
  5. DistilBERT · recommended 1×
  • CATEGORY QUERY
    What are the available transformer models for various natural language processing tasks and applications?
    you: not recommended
    AI recommended (in order):
    1. BERT
    2. RoBERTa
    3. GPT-3 / GPT-4
    4. T5
    5. DistilBERT
    6. BART
    7. ELECTRA

    AI recommended 7 alternatives but never named abacaj/awesome-transformers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a curated list to compare different large language model architectures and their licenses?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Models Page
    2. Papers With Code
    3. Wikipedia
    4. GitHub Repositories
    5. Llama 2
    6. Gemma

    AI recommended 6 alternatives but never named abacaj/awesome-transformers. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    Suggestion:

  • 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 abacaj/awesome-transformers?
    pass
    AI did not name abacaj/awesome-transformers — 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 abacaj/awesome-transformers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named abacaj/awesome-transformers 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 abacaj/awesome-transformers solve, and who is the primary audience?
    pass
    AI did not name abacaj/awesome-transformers — 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?

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