RRepoGEO

REPOGEO REPORT · LITE

wenge-research/YAYI2

Default branch main · commit 7ee4d9e3 · scanned 5/13/2026, 10:27:40 AM

GitHub: 2,801 stars · 18 forks

AI VISIBILITY SCORE
35 /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
3 / 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 wenge-research/YAYI2, 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 the core introduction to the top of the README

    Why:

    CURRENT
    The README currently starts with a div, links, and '## 更新' (Updates) before '## 介绍' (Introduction).
    COPY-PASTE FIX
    Move the entire content of the '## 介绍' section to appear immediately after any initial badges or title, and before the '## 更新' section. The content is:
    
    YAYI 2 是中科闻歌研发的**新一代开源大语言模型**,包括 Base 和 Chat 版本,参数规模为 30B。YAYI2-30B 是基于 Transformer 的大语言模型,采用了超过 2 万亿 Tokens 的高质量、多语言语料进行预训练。针对通用和特定领域的应用场景,我们采用了百万级指令进行微调,同时借助人类反馈强化学习方法,以更好地使模型与人类价值观对齐。
    
    本次开源的模型为 YAYI2-30B Base 模型。我们希望通过雅意大模型的开源来促进中文预训练大模型开源社区的发展,并积极为此做出贡献。通过开源,我们与每一位合作伙伴共同构建雅意大模型生态。
    
    更多技术细节,欢迎阅读我们的技术报告🔥YAYI 2: Multilingual Open-Source Large Language Models。
  • highhomepage#2
    Add the project homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add the URL that the '[🔗网页端]' link in your README points to, or your primary project page, to the 'Homepage' field in your repository settings.
  • mediumtopics#3
    Expand repository topics with more specific keywords

    Why:

    CURRENT
    artificial-intelligence, chat, chinese, gpt, natural-language-generation, pretrained-language-model, yayi
    COPY-PASTE FIX
    Add the following topics: multilingual, foundation-model, llm. The full list should be: artificial-intelligence, chat, chinese, gpt, natural-language-generation, pretrained-language-model, yayi, multilingual, foundation-model, llm

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 wenge-research/YAYI2
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mistralai/mistral-src
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. mistralai/mistral-src · recommended 2×
  2. Baichuan 2 · recommended 1×
  3. Qwen · recommended 1×
  4. ChatGLM3 · recommended 1×
  5. Yi · recommended 1×
  • CATEGORY QUERY
    Looking for an open-source large language model specifically optimized for Chinese text generation.
    you: not recommended
    AI recommended (in order):
    1. Baichuan 2
    2. Qwen
    3. ChatGLM3
    4. Yi
    5. Pangu-Σ

    AI recommended 5 alternatives but never named wenge-research/YAYI2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are powerful open-source foundation models suitable for general-purpose chat applications?
    you: not recommended
    AI recommended (in order):
    1. Llama 3 (facebookresearch/llama)
    2. Mixtral 8x7B (mistralai/mistral-src)
    3. Gemma (google/gemma.cpp)
    4. Mistral 7B Instruct (mistralai/mistral-src)
    5. Falcon 40B Instruct (tiiuae/falcon-40b)

    AI recommended 5 alternatives but never named wenge-research/YAYI2. 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 wenge-research/YAYI2?
    pass
    AI named wenge-research/YAYI2 explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts wenge-research/YAYI2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wenge-research/YAYI2 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 wenge-research/YAYI2 solve, and who is the primary audience?
    pass
    AI named wenge-research/YAYI2 explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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wenge-research/YAYI2 — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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