RRepoGEO

REPOGEO REPORT · LITE

ymcui/Chinese-LLaMA-Alpaca-3

Default branch main · commit 0f39d4a8 · scanned 5/12/2026, 1:38:00 PM

GitHub: 1,970 stars · 170 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 ymcui/Chinese-LLaMA-Alpaca-3, 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 prominent, competitive opening statement to README

    Why:

    COPY-PASTE FIX
    ymcui/Chinese-LLaMA-Alpaca-3 is the leading open-source project for Chinese Llama-3 LLMs, offering advanced base and instruction-tuned models for Chinese NLP and instruction following.
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://[your-project-homepage-url-here]
  • lowtopics#3
    Add more specific topics for Chinese LLMs and instruction tuning

    Why:

    CURRENT
    alpaca, large-language-models, llama, llama-2, llama-3, llama3, llm, nlp
    COPY-PASTE FIX
    alpaca, large-language-models, llama, llama-2, llama-3, llama3, llm, nlp, chinese-llm, chinese-nlp, instruction-tuning, fine-tuning

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 ymcui/Chinese-LLaMA-Alpaca-3
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Qwen
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Qwen · recommended 1×
  2. ChatGLM · recommended 1×
  3. Baichuan · recommended 1×
  4. InternLM · recommended 1×
  5. Yi · recommended 1×
  • CATEGORY QUERY
    What are the best open-source large language models for Chinese natural language processing?
    you: not recommended
    AI recommended (in order):
    1. Qwen
    2. ChatGLM
    3. Baichuan
    4. InternLM
    5. Yi

    AI recommended 5 alternatives but never named ymcui/Chinese-LLaMA-Alpaca-3. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I fine-tune a powerful LLM to improve its performance on Chinese instruction following?
    you: not recommended
    AI recommended (in order):
    1. Qwen2
    2. Hugging Face Transformers
    3. PEFT
    4. Baichuan2
    5. LLaMA 3
    6. Mistral Large
    7. Mixtral 8x22B
    8. InternLM2
    9. TRL

    AI recommended 9 alternatives but never named ymcui/Chinese-LLaMA-Alpaca-3. 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 ymcui/Chinese-LLaMA-Alpaca-3?
    pass
    AI did not name ymcui/Chinese-LLaMA-Alpaca-3 — 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 ymcui/Chinese-LLaMA-Alpaca-3 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ymcui/Chinese-LLaMA-Alpaca-3 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 ymcui/Chinese-LLaMA-Alpaca-3 solve, and who is the primary audience?
    pass
    AI did not name ymcui/Chinese-LLaMA-Alpaca-3 — 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

Drop this badge into the README of ymcui/Chinese-LLaMA-Alpaca-3. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
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HTML
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ymcui/Chinese-LLaMA-Alpaca-3 — 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