RRepoGEO

REPOGEO REPORT · LITE

huggingface/naacl_transfer_learning_tutorial

Default branch master · commit dc976775 · scanned 6/8/2026, 3:47:19 PM

GitHub: 723 stars · 121 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 huggingface/naacl_transfer_learning_tutorial, 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 to clarify its tutorial nature

    Why:

    CURRENT
    # Code repository accompanying NAACL 2019 tutorial on "Transfer Learning in Natural Language Processing"
    COPY-PASTE FIX
    # Code Repository for the NAACL 2019 Tutorial on Transfer Learning in NLP
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://tinyurl.com/NAACLTransferColab
  • lowtopics#3
    Add more specific topics to highlight practical code examples

    Why:

    CURRENT
    naacl, nlp, transfer-learning, tutorial
    COPY-PASTE FIX
    naacl, nlp, transfer-learning, tutorial, code-examples, hands-on

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 huggingface/naacl_transfer_learning_tutorial
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. DistilBERT · recommended 1×
  4. XLM-RoBERTa · recommended 1×
  5. GPT-2 · recommended 1×
  • CATEGORY QUERY
    How to apply transfer learning techniques for natural language processing tasks?
    you: not recommended
    AI recommended (in order):
    1. BERT
    2. RoBERTa
    3. DistilBERT
    4. XLM-RoBERTa
    5. GPT-2
    6. GPT-3.5
    7. GPT-4
    8. Sentence-BERT (SBERT)
    9. Universal Sentence Encoder (USE)
    10. BioBERT
    11. SciBERT

    AI recommended 11 alternatives but never named huggingface/naacl_transfer_learning_tutorial. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find practical code examples for transfer learning in NLP?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library (huggingface/transformers)
    2. Kaggle
    3. PyTorch (pytorch/examples)
    4. TensorFlow Hub
    5. Fast.ai (fastai/fastbook)
    6. Medium

    AI recommended 6 alternatives but never named huggingface/naacl_transfer_learning_tutorial. 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 huggingface/naacl_transfer_learning_tutorial?
    pass
    AI did not name huggingface/naacl_transfer_learning_tutorial — 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 huggingface/naacl_transfer_learning_tutorial in production, what risks or prerequisites should they evaluate first?
    pass
    AI named huggingface/naacl_transfer_learning_tutorial 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 huggingface/naacl_transfer_learning_tutorial solve, and who is the primary audience?
    pass
    AI did not name huggingface/naacl_transfer_learning_tutorial — 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?

Embed your GEO score

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huggingface/naacl_transfer_learning_tutorial — 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