RRepoGEO

REPOGEO REPORT · LITE

cedrickchee/awesome-transformer-nlp

Default branch master · commit 594ec55d · scanned 5/20/2026, 1:32:46 AM

GitHub: 1,137 stars · 135 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
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 cedrickchee/awesome-transformer-nlp, 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 opening to emphasize its role as a guide

    Why:

    CURRENT
    This repository contains a hand-curated list of great machine (deep) learning resources for Natural Language Processing (NLP) with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, ChatGPT, and transfer learning in NLP.
    COPY-PASTE FIX
    This comprehensive, hand-curated list serves as your ultimate guide to the best machine (deep) learning resources for Natural Language Processing (NLP), with a focus on Generative Pre-trained Transformer (GPT), Bidirectional Encoder Representations from Transformers (BERT), attention mechanism, Transformer architectures/networks, ChatGPT, and transfer learning in NLP. It's designed to be your go-to starting point for exploring the vast landscape of Transformer-based NLP.
  • mediumhomepage#2
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/cedrickchee/awesome-transformer-nlp
  • lowtopics#3
    Add topics emphasizing 'learning' and 'guide' aspects

    Why:

    CURRENT
    attention-mechanism, awesome, awesome-list, bert, chatgpt, gpt-2, gpt-3, gpt-4, language-model, llama, natural-language-processing, neural-networks, nlp, pre-trained-language-models, transfer-learning, transformer, xlnet
    COPY-PASTE FIX
    attention-mechanism, awesome, awesome-list, bert, chatgpt, gpt-2, gpt-3, gpt-4, language-model, llama, natural-language-processing, neural-networks, nlp, nlp-learning, ai-guide, deep-learning-guide, pre-trained-language-models, transfer-learning, transformer, xlnet

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 cedrickchee/awesome-transformer-nlp
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 2×
  2. Attention Is All You Need · recommended 1×
  3. Jay Alammar's Blog Posts · recommended 1×
  4. Stanford CS224N · recommended 1×
  5. fastai/fastai · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive resources on transformer networks, BERT, and large language models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library (huggingface/transformers)
    2. Attention Is All You Need
    3. Jay Alammar's Blog Posts
    4. Stanford CS224N
    5. fastai (fastai/fastai)
    6. Natural Language Processing with Transformers
    7. Google AI Blog

    AI recommended 7 alternatives but never named cedrickchee/awesome-transformer-nlp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best learning materials for attention mechanisms and transfer learning in modern NLP?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library (huggingface/transformers)

    AI recommended 1 alternative but never named cedrickchee/awesome-transformer-nlp. 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 cedrickchee/awesome-transformer-nlp?
    pass
    AI did not name cedrickchee/awesome-transformer-nlp — 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 cedrickchee/awesome-transformer-nlp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cedrickchee/awesome-transformer-nlp 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 cedrickchee/awesome-transformer-nlp solve, and who is the primary audience?
    pass
    AI did not name cedrickchee/awesome-transformer-nlp — 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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cedrickchee/awesome-transformer-nlp — 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