RRepoGEO

REPOGEO REPORT · LITE

kohya-ss/musubi-tuner

Default branch main · commit 9bfc5a48 · scanned 6/18/2026, 9:11:45 AM

GitHub: 1,864 stars · 281 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)

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

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 kohya-ss/musubi-tuner, 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
  • highabout#1
    Add a concise description to the repository's About section

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Optimizes hyperparameters for LoRA training, specifically for generative models like Stable Diffusion, HunyuanVideo, and Wan2.1/2.2.
  • highlicense#2
    Create a LICENSE file and clarify license in README

    Why:

    CURRENT
    License: (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0). Then, update the 'License' section in `README.md` to explicitly state the license(s) that apply, for example: 'This project is licensed under the MIT License - see the LICENSE file for details.'

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 kohya-ss/musubi-tuner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Lightning
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Lightning · recommended 1×
  2. Keras · recommended 1×
  3. TensorFlow Datasets · recommended 1×
  4. Weights & Biases · recommended 1×
  5. DVC · recommended 1×
  • CATEGORY QUERY
    What tools help with configuring datasets and training deep learning models efficiently?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Lightning
    2. Keras
    3. TensorFlow Datasets
    4. Weights & Biases
    5. DVC
    6. Optuna

    AI recommended 6 alternatives but never named kohya-ss/musubi-tuner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a framework to streamline model pre-caching, training, and inference workflows.
    you: not recommended
    AI recommended (in order):
    1. MLflow (mlflow/mlflow)
    2. Kubeflow (kubeflow/kubeflow)
    3. Metaflow (Netflix/metaflow)
    4. DVC (iterative/dvc)
    5. Ray (ray-project/ray)
    6. Pachyderm (pachyderm/pachyderm)

    AI recommended 6 alternatives but never named kohya-ss/musubi-tuner. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 kohya-ss/musubi-tuner?
    pass
    AI did not name kohya-ss/musubi-tuner — 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?

  • If a team adopts kohya-ss/musubi-tuner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kohya-ss/musubi-tuner 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 kohya-ss/musubi-tuner solve, and who is the primary audience?
    pass
    AI named kohya-ss/musubi-tuner 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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kohya-ss/musubi-tuner — 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