RRepoGEO

REPOGEO REPORT · LITE

lucidrains/transfusion-pytorch

Default branch main · commit 04707daa · scanned 6/23/2026, 10:47:01 PM

GitHub: 1,375 stars · 73 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
35 /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
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 lucidrains/transfusion-pytorch, 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 specific generative AI topics

    Why:

    CURRENT
    artificial-intelligence, attention, deep-learning, flow-matching, multi-modal, transformers
    COPY-PASTE FIX
    artificial-intelligence, attention, deep-learning, flow-matching, multi-modal, transformers, generative-ai, content-generation, image-generation, text-generation
  • mediumhomepage#2
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/lucidrains/transfusion-pytorch
  • lowreadme#3
    Slightly rephrase README opening to emphasize generative capabilities

    Why:

    CURRENT
    Pytorch implementation of Transfusion, "Predict the Next Token and Diffuse Images with One Multi-Modal Model", from MetaAI.
    COPY-PASTE FIX
    PyTorch implementation of Transfusion, a multi-modal generative model from MetaAI, capable of predicting tokens and diffusing images. This repository focuses on implementing the "Predict the Next Token and Diffuse Images with One Multi-Modal Model" approach.

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 lucidrains/transfusion-pytorch
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepSpeed
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepSpeed · recommended 2×
  2. Hugging Face Transformers Library · recommended 1×
  3. DALL-E 2 · recommended 1×
  4. Craiyon · recommended 1×
  5. Stable Diffusion · recommended 1×
  • CATEGORY QUERY
    Need a PyTorch solution for multi-modal content generation across text and images.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library
    2. DALL-E 2
    3. Craiyon
    4. Stable Diffusion
    5. BLIP
    6. CLIP
    7. PyTorch-Lightning
    8. Hugging Face Diffusers
    9. OpenAI CLIP
    10. MinDALL-E
    11. DeepSpeed
    12. FSDP

    AI recommended 12 alternatives but never named lucidrains/transfusion-pytorch. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good PyTorch libraries for multi-modal transformer architectures with generative capabilities?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. OpenAI's DALL-E
    3. PyTorch-Image-Models (timm)
    4. DeepSpeed
    5. FairScale
    6. x-transformers
    7. torchvision

    AI recommended 7 alternatives but never named lucidrains/transfusion-pytorch. 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 lucidrains/transfusion-pytorch?
    pass
    AI named lucidrains/transfusion-pytorch explicitly

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

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

    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 lucidrains/transfusion-pytorch. 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/lucidrains/transfusion-pytorch.svg)](https://repogeo.com/en/r/lucidrains/transfusion-pytorch)
HTML
<a href="https://repogeo.com/en/r/lucidrains/transfusion-pytorch"><img src="https://repogeo.com/badge/lucidrains/transfusion-pytorch.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

lucidrains/transfusion-pytorch — 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