RRepoGEO

REPOGEO REPORT · LITE

Separius/BERT-keras

Default branch master · commit 76bd737c · scanned 6/11/2026, 10:43:12 AM

GitHub: 813 stars · 190 forks

AI VISIBILITY SCORE
28 /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
2 / 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 Separius/BERT-keras, 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
    Reframe the 'Archive' status in the README

    Why:

    CURRENT
    **Status:** Archive (code is provided as-is, no updates expected)
    COPY-PASTE FIX
    **Status:** Archived (code is provided as-is for historical reference and learning, no active updates expected). This repository remains a valuable resource for those seeking a pure Keras implementation of BERT and OpenAI's Transformer LM.
  • highreadme#2
    Strengthen the README's opening to highlight its pure Keras niche

    Why:

    CURRENT
    # BERT-keras
Keras implementation of Google BERT(Bidirectional Encoder Representations from Transformers) and OpenAI's Transformer LM capable of loading pretrained models with a finetuning API.
    COPY-PASTE FIX
    # BERT-keras
This repository provides a pure Keras implementation of Google BERT (Bidirectional Encoder Representations from Transformers) and OpenAI's Transformer LM, capable of loading pretrained models with a finetuning API. Unlike multi-framework libraries, BERT-keras focuses on a native Keras experience, ideal for Keras-centric projects or educational purposes.
  • mediumabout#3
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    https://github.com/Separius/BERT-keras

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 Separius/BERT-keras
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. Keras · recommended 2×
  3. spaCy · recommended 1×
  4. Flair · recommended 1×
  5. TensorFlow Hub · recommended 1×
  • CATEGORY QUERY
    Seeking a Python library for applying pre-trained deep learning models to diverse natural language tasks.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. Flair
    4. Keras
    5. TensorFlow Hub
    6. PyTorch

    AI recommended 6 alternatives but never named Separius/BERT-keras. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good options for fine-tuning transformer-based models for custom language understanding applications?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch Lightning
    3. Keras
    4. Fast.ai
    5. Ludwig

    AI recommended 5 alternatives but never named Separius/BERT-keras. 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 Separius/BERT-keras?
    pass
    AI named Separius/BERT-keras explicitly

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

  • If a team adopts Separius/BERT-keras in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Separius/BERT-keras 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 Separius/BERT-keras solve, and who is the primary audience?
    pass
    AI did not name Separius/BERT-keras — 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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Separius/BERT-keras — 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