RRepoGEO

REPOGEO REPORT · LITE

datawhalechina/llms-from-scratch-cn

Default branch main · commit 6ca2631b · scanned 5/13/2026, 7:08:04 PM

GitHub: 4,143 stars · 572 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 datawhalechina/llms-from-scratch-cn, 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
    Add a clear positioning statement to the README's introduction

    Why:

    CURRENT
    如果你想从0手写代码，构建大语言模型，本项目很适合你。本项目 "LLMs From Scratch" 是由 Datawhale 提供的一个从头开始构建类似 ChatGPT 大型语言模型（LLM）的实践教程。
    COPY-PASTE FIX
    本项目 "LLMs From Scratch" 是 Datawhale 提供的**一套实践教程**，旨在帮助你**从零开始，亲手实现**大语言模型（LLM）的核心原理和架构，**而非仅仅使用或微调现有框架**。通过本教程，你将深入理解LLM的内部工作机制。
  • mediumreadme#2
    Clarify the repository's license in the README

    Why:

    COPY-PASTE FIX
    ## 📄 许可协议
本项目遵循 `LICENSE.txt` 文件中定义的许可协议。请查阅该文件以获取详细的许可条款和条件。
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/datawhalechina/llms-from-scratch-cn

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 datawhalechina/llms-from-scratch-cn
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. PyTorch · recommended 2×
  3. TensorFlow · recommended 2×
  4. JAX · recommended 2×
  5. transformers library · recommended 1×
  • CATEGORY QUERY
    How can I learn to build large language models from scratch using Python?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch
    3. TensorFlow
    4. transformers library
    5. datasets library
    6. tokenizers library
    7. nanoGPT (karpathy/nanoGPT)
    8. JAX
    9. Flax
    10. DeepSpeed
    11. PyTorch FSDP
    12. Keras

    AI recommended 12 alternatives but never named datawhalechina/llms-from-scratch-cn. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking resources to deeply understand large language model principles by implementing them from scratch.
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. JAX
    4. NumPy
    5. Hugging Face Transformers

    AI recommended 5 alternatives but never named datawhalechina/llms-from-scratch-cn. 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 datawhalechina/llms-from-scratch-cn?
    pass
    AI did not name datawhalechina/llms-from-scratch-cn — 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 datawhalechina/llms-from-scratch-cn in production, what risks or prerequisites should they evaluate first?
    pass
    AI named datawhalechina/llms-from-scratch-cn 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 datawhalechina/llms-from-scratch-cn solve, and who is the primary audience?
    pass
    AI did not name datawhalechina/llms-from-scratch-cn — 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite