RRepoGEO

REPOGEO REPORT · LITE

candle-org/mindnlp

Default branch master · commit 7dd3e355 · scanned 6/16/2026, 11:06:51 PM

GitHub: 919 stars · 270 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 candle-org/mindnlp, 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 README's first tagline to emphasize deep learning framework bridging

    Why:

    CURRENT
    <p align="center">
  <strong>Run HuggingFace Models on MindSpore with Zero Code Changes</strong>
</p>
    COPY-PASTE FIX
    <p align="center">
  <strong>Bridge HuggingFace Models to the MindSpore Deep Learning Framework with Zero Code Changes</strong>
</p>
  • mediumreadme#2
    Add a dedicated 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## 🤝 Comparison with Alternatives

Unlike deployment-focused tools like ONNX Runtime, OpenVINO, or TensorFlow Lite, MindNLP is a deep learning library designed to enable seamless execution of HuggingFace models directly within the MindSpore framework. We focus on framework compatibility and acceleration for MindSpore users, rather than general model optimization for diverse hardware backends.
  • lowtopics#3
    Add a topic for framework interoperability

    Why:

    CURRENT
    deep-learning, diffusion-models, huggingface, large-language-models, llm, mindspore, natural-language-processing, nlp, nlp-library, python, vlm
    COPY-PASTE FIX
    deep-learning, diffusion-models, framework-interoperability, huggingface, large-language-models, llm, mindspore, natural-language-processing, nlp, nlp-library, python, vlm

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 candle-org/mindnlp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ONNX Runtime
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ONNX Runtime · recommended 2×
  2. TensorFlow Lite · recommended 2×
  3. OpenVINO Toolkit · recommended 1×
  4. Apache TVM · recommended 1×
  5. MNN · recommended 1×
  • CATEGORY QUERY
    How can I run popular language models from a common ecosystem on an alternative deep learning framework?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit
    2. ONNX Runtime
    3. TensorFlow Lite
    4. Apache TVM
    5. MNN
    6. NVIDIA TensorRT

    AI recommended 6 alternatives but never named candle-org/mindnlp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a library to adapt existing transformer models for different deep learning backends and hardware acceleration.
    you: not recommended
    AI recommended (in order):
    1. OpenVINO
    2. ONNX Runtime
    3. TensorRT
    4. TVM
    5. DeepSpeed
    6. Accelerate
    7. PyTorch Mobile
    8. TensorFlow Lite

    AI recommended 8 alternatives but never named candle-org/mindnlp. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 candle-org/mindnlp?
    pass
    AI named candle-org/mindnlp explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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HTML
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candle-org/mindnlp — 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