RRepoGEO

REPOGEO REPORT · LITE

nathan-barry/tiny-diffusion

Default branch main · commit 667853bc · scanned 6/7/2026, 4:06:51 AM

GitHub: 906 stars · 86 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 nathan-barry/tiny-diffusion, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    diffusion-models, text-generation, character-level, language-model, pytorch, educational, minimalist, tiny-models
  • highreadme#2
    Reposition the README's opening sentence to clarify educational purpose

    Why:

    CURRENT
    A character-level language diffusion model for text generation trained on Tiny Shakespeare, in 365 lines of code! It is only 10.7 million parameters, so you can also try it out locally!
    COPY-PASTE FIX
    A minimal, educational character-level language diffusion model for text generation, implemented in just 365 lines of PyTorch code and trained on Tiny Shakespeare. It's designed for local experimentation and learning about diffusion models.
  • mediumhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/nathan-barry/tiny-diffusion

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 nathan-barry/tiny-diffusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
diffusers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. diffusers · recommended 1×
  2. PyTorch · recommended 1×
  3. TensorFlow/Keras · recommended 1×
  4. minDiffusion · recommended 1×
  5. nanoGPT · recommended 1×
  • CATEGORY QUERY
    How to implement a small character-level text generation diffusion model locally for experimentation?
    you: not recommended
    AI recommended (in order):
    1. diffusers
    2. PyTorch
    3. TensorFlow/Keras
    4. minDiffusion
    5. nanoGPT

    AI recommended 5 alternatives but never named nathan-barry/tiny-diffusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are lightweight text generation models, besides GPT, suitable for local character-level tasks?
    you: not recommended
    AI recommended (in order):
    1. NanoGPT
    2. Char-RNN
    3. TinyLlama
    4. Pythia
    5. DistilGPT2
    6. BLOOMZ

    AI recommended 6 alternatives but never named nathan-barry/tiny-diffusion. 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 nathan-barry/tiny-diffusion?
    pass
    AI named nathan-barry/tiny-diffusion explicitly

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

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

Embed your GEO score

Drop this badge into the README of nathan-barry/tiny-diffusion. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/nathan-barry/tiny-diffusion.svg)](https://repogeo.com/en/r/nathan-barry/tiny-diffusion)
HTML
<a href="https://repogeo.com/en/r/nathan-barry/tiny-diffusion"><img src="https://repogeo.com/badge/nathan-barry/tiny-diffusion.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

nathan-barry/tiny-diffusion — 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