RRepoGEO

REPOGEO REPORT · LITE

wangyuxinwhy/uniem

Default branch main · commit f76acf92 · scanned 5/29/2026, 8:06:55 PM

GitHub: 878 stars · 72 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 wangyuxinwhy/uniem, 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 README's opening sentence to emphasize framework capabilities

    Why:

    CURRENT
    uniem 项目的目标是创建中文最好的通用文本嵌入模型。
    COPY-PASTE FIX
    uniem 是一个专注于中文文本嵌入模型的统一框架，旨在提供训练、微调和评测中文最佳通用文本嵌入模型的工具和代码。
  • mediumabout#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add the URL to the project's main documentation site or its primary Hugging Face organization page (e.g., 'https://huggingface.co/uniem' if applicable) to the repository's 'Homepage' field in the 'About' section.
  • lowtopics#3
    Refine repository topics to highlight framework and fine-tuning aspects

    Why:

    CURRENT
    embeddings, huggingface, nlp, sentence-embeddings, sentence-transformers
    COPY-PASTE FIX
    embeddings, huggingface, nlp, sentence-embeddings, sentence-transformers, finetuning, model-training, evaluation-framework, chinese-nlp

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 wangyuxinwhy/uniem
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
m3e-base
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. m3e-base · recommended 1×
  2. BGE-Large-zh-v1.5 · recommended 1×
  3. text2vec-large-chinese · recommended 1×
  4. SimCSE-Chinese-RoBERTa-wwm-ext · recommended 1×
  5. ERNIE-Gram-zh · recommended 1×
  • CATEGORY QUERY
    What are good general-purpose text embedding models specifically optimized for Chinese language?
    you: not recommended
    AI recommended (in order):
    1. m3e-base
    2. BGE-Large-zh-v1.5
    3. text2vec-large-chinese
    4. SimCSE-Chinese-RoBERTa-wwm-ext
    5. ERNIE-Gram-zh

    AI recommended 5 alternatives but never named wangyuxinwhy/uniem. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to easily fine-tune existing text embedding models for domain-specific applications?
    you: not recommended
    AI recommended (in order):
    1. Sentence-BERT (SBERT) (UKPLab/sentence-transformers)
    2. Hugging Face Transformers (huggingface/transformers)
    3. SetFit (huggingface/setfit)
    4. OpenAI API
    5. Haystack (deepset-ai/haystack)
    6. DeepSpeed (microsoft/DeepSpeed)
    7. PyTorch FSDP (pytorch/pytorch)

    AI recommended 7 alternatives but never named wangyuxinwhy/uniem. 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 wangyuxinwhy/uniem?
    pass
    AI named wangyuxinwhy/uniem explicitly

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

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

    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 wangyuxinwhy/uniem. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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wangyuxinwhy/uniem — 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
wangyuxinwhy/uniem — RepoGEO report