RRepoGEO

REPOGEO REPORT · LITE

terrifyzhao/bert-utils

Default branch master · commit 1d5f3eb6 · scanned 5/25/2026, 10:58:12 AM

GitHub: 1,671 stars · 422 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 terrifyzhao/bert-utils, 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
    Clarify README opening to specify original BERT context

    Why:

    CURRENT
    本文基于Google开源的BERT代码进行了进一步的简化，方便生成句向量与做文本分类
    COPY-PASTE FIX
    本项目是**Google官方开源BERT代码的实用工具集**，旨在提供**最直接、最简化的接口**，方便用户快速进行句向量生成、文本分类和文本相似度计算，**尤其适合需要基于原始BERT实现进行开发或迁移的场景**。
  • mediumtopics#2
    Add relevant topics for discoverability

    Why:

    COPY-PASTE FIX
    bert, nlp, sentence-embeddings, text-classification, text-similarity, google-bert
  • lowhomepage#3
    Add a homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/terrifyzhao/bert-utils

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 terrifyzhao/bert-utils
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Sentence Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Sentence Transformers · recommended 1×
  2. Hugging Face Transformers · recommended 1×
  3. Flair · recommended 1×
  4. Keras/TensorFlow Hub · recommended 1×
  5. PyTorch-Transformers · recommended 1×
  • CATEGORY QUERY
    What's a straightforward Python library for generating BERT sentence embeddings?
    you: not recommended
    AI recommended (in order):
    1. Sentence Transformers
    2. Hugging Face Transformers
    3. Flair
    4. Keras/TensorFlow Hub
    5. PyTorch-Transformers

    AI recommended 5 alternatives but never named terrifyzhao/bert-utils. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I quickly fine-tune a BERT model for custom text classification?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library
    2. Keras
    3. TensorFlow Hub
    4. PyTorch Lightning
    5. Simple Transformers
    6. fast.ai

    AI recommended 6 alternatives but never named terrifyzhao/bert-utils. 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 terrifyzhao/bert-utils?
    pass
    AI named terrifyzhao/bert-utils explicitly

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

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

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

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terrifyzhao/bert-utils — 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