RRepoGEO

REPOGEO REPORT · LITE

cloneofsimo/lora

Default branch master · commit d84074b3 · scanned 6/29/2026, 12:51:48 PM

GitHub: 7,542 stars · 494 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
92 /100
Healthy
Category recall
2 / 2
Avg rank #1.0 when recommended
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 cloneofsimo/lora, 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
  • mediumreadme#1
    Add a concise introductory sentence to the README

    Why:

    CURRENT
    The README currently starts with the H1 followed by visual examples and a formula.
    COPY-PASTE FIX
    After the H1 `# Low-rank Adaptation for Fast Text-to-Image Diffusion Fine-tuning`, add a sentence like: "This repository provides an efficient and lightweight implementation of Low-rank Adaptation (LoRA) for quickly fine-tuning text-to-image diffusion models, enabling faster training and significantly smaller output files compared to traditional methods."
  • mediumtopics#2
    Add 'peft' to repository topics

    Why:

    CURRENT
    diffusion, dreambooth, fine-tuning, lora, stable-diffusion
    COPY-PASTE FIX
    diffusion, dreambooth, fine-tuning, lora, stable-diffusion, peft
  • lowcomparison#3
    Add a dedicated comparison section in the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example, `## Comparison with Alternatives`, detailing how LoRA differentiates from DreamBooth, QLoRA, and full fine-tuning in terms of speed, model size, and performance.

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
2 / 2
100% of queries surface cloneofsimo/lora
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
13%
Of all named tools, what % are you?
Top rival
DreamBooth
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DreamBooth · recommended 2×
  2. QLoRA · recommended 2×
  3. Hypernetworks · recommended 2×
  4. AUTOMATIC1111/stable-diffusion-webui · recommended 1×
  5. kohya-ss/sd-scripts · recommended 1×
  • CATEGORY QUERY
    How to efficiently fine-tune stable diffusion models for custom styles with small output files?
    you: #1
    AI recommended (in order):
    1. LoRA ← you
    2. Automatic1111's web UI (AUTOMATIC1111/stable-diffusion-webui)
    3. Kohya's GUI (kohya-ss/sd-scripts)
    4. DreamBooth
    5. Textual Inversion
    6. ControlNet (lllyasviel/ControlNet)
    7. ComfyUI (comfyanonymous/ComfyUI)
    8. QLoRA
    9. Hypernetworks
    Show full AI answer
  • CATEGORY QUERY
    What are the best methods for fast, low-rank adaptation of text-to-image diffusion models?
    you: #1
    AI recommended (in order):
    1. LoRA ← you
    2. DreamBooth
    3. ControlNet
    4. QLoRA
    5. AdaLoRA
    6. P-tuning v2
    7. Hypernetworks
    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 cloneofsimo/lora?
    pass
    AI named cloneofsimo/lora explicitly

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

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

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

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cloneofsimo/lora — 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