RRepoGEO

REPOGEO REPORT · LITE

fastino-ai/GLiNER2

Default branch main · commit 3feddeee · scanned 6/26/2026, 12:47:03 AM

GitHub: 1,643 stars · 149 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 fastino-ai/GLiNER2, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highhomepage#1
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://pioneer.ai/gliner
  • mediumabout#2
    Expand the 'About' description with key differentiators

    Why:

    CURRENT
    Unified Schema-Based Information Extraction
    COPY-PASTE FIX
    GLiNER2 unifies Named Entity Recognition, Text Classification, Structured Data Extraction, and Relation Extraction into a single efficient model, providing CPU-first inference without external API dependencies.

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 fastino-ai/GLiNER2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
spaCy
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. spaCy · recommended 2×
  2. Hugging Face Transformers · recommended 2×
  3. NLTK · recommended 2×
  4. TextBlob · recommended 1×
  5. Gensim · recommended 1×
  • CATEGORY QUERY
    How can I extract entities and classify text efficiently on CPU without external APIs?
    you: not recommended
    AI recommended (in order):
    1. spaCy
    2. Hugging Face Transformers
    3. NLTK
    4. TextBlob
    5. Gensim
    6. scikit-learn

    AI recommended 6 alternatives but never named fastino-ai/GLiNER2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help extract structured information from text using a schema locally on standard hardware?
    you: not recommended
    AI recommended (in order):
    1. spaCy
    2. SetFit
    3. Haystack (deepset/Haystack)
    4. OpenNMT-py
    5. Hugging Face Transformers
    6. NLTK
    7. Rasa NLU

    AI recommended 7 alternatives but never named fastino-ai/GLiNER2. 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 fastino-ai/GLiNER2?
    pass
    AI named fastino-ai/GLiNER2 explicitly

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

  • If a team adopts fastino-ai/GLiNER2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named fastino-ai/GLiNER2 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 fastino-ai/GLiNER2 solve, and who is the primary audience?
    pass
    AI named fastino-ai/GLiNER2 explicitly

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

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fastino-ai/GLiNER2 — 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