RRepoGEO

REPOGEO REPORT · LITE

openai/image-gpt

Default branch master · commit c6af2ebf · scanned 5/15/2026, 8:08:07 PM

GitHub: 2,088 stars · 388 forks

AI VISIBILITY SCORE
17 /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
1 / 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 openai/image-gpt, 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
  • highabout#1
    Add a concise description to the repository's About section

    Why:

    COPY-PASTE FIX
    Code and models for 'Generative Pretraining from Pixels', demonstrating how GPT-like transformer architectures can be applied to unconditional image generation from pixel data.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    image-generation, generative-ai, transformers, gpt, computer-vision, deep-learning, pixel-data
  • highreadme#3
    Reposition the README's opening to clearly state the project's purpose

    Why:

    CURRENT
    **Status:** Archive (code is provided as-is, no updates expected)

# image-gpt

Code and models from the paper "Generative Pretraining from Pixels".
    COPY-PASTE FIX
    # image-gpt: Generative Pretraining from Pixels

This repository provides the original code and models from the paper "Generative Pretraining from Pixels", demonstrating how GPT-like transformer architectures can be applied to unconditional image generation directly from pixel data. It serves as a research artifact for those exploring generative AI in computer vision. **Status:** Archive (code is provided as-is, no updates expected).

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 openai/image-gpt
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
rwightman/pytorch-image-models
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. rwightman/pytorch-image-models · recommended 1×
  2. huggingface/diffusers · recommended 1×
  3. eriklindernoren/Keras-GAN · recommended 1×
  4. OpenAI's Jukebox/DALL-E repositories · recommended 1×
  5. tensorflow/gan · recommended 1×
  • CATEGORY QUERY
    What are good libraries for generative image pretraining using pixel data?
    you: not recommended
    AI recommended (in order):
    1. PyTorch-Image-Models (timm) (rwightman/pytorch-image-models)
    2. Diffusers (Hugging Face) (huggingface/diffusers)
    3. Keras-GAN (eriklindernoren/Keras-GAN)
    4. OpenAI's Jukebox/DALL-E repositories
    5. TensorFlow-GAN (TFGAN) (tensorflow/gan)
    6. StyleGAN3 (NVIDIA) (NVlabs/stylegan3)

    AI recommended 6 alternatives but never named openai/image-gpt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I adapt transformer models, similar to GPT, for image synthesis tasks?
    you: not recommended
    AI recommended (in order):
    1. DALL-E
    2. VQGAN
    3. minDALL-E
    4. Parti
    5. Perceiver IO
    6. ImageGPT
    7. PyTorch
    8. TensorFlow
    9. Hugging Face Transformers

    AI recommended 9 alternatives but never named openai/image-gpt. 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 openai/image-gpt?
    pass
    AI did not name openai/image-gpt — 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 openai/image-gpt in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/image-gpt 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 openai/image-gpt solve, and who is the primary audience?
    pass
    AI did not name openai/image-gpt — 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

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
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