RRepoGEO

REPOGEO REPORT · LITE

ritheshkumar95/pytorch-vqvae

Default branch master · commit 8d123c0d · scanned 6/4/2026, 1:12:48 PM

GitHub: 955 stars · 140 forks

AI VISIBILITY SCORE
22 /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
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 ritheshkumar95/pytorch-vqvae, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the text of a standard open-source license, such as the MIT License.
  • highreadme#2
    Reposition the README's opening to clearly state its purpose as a PyTorch implementation

    Why:

    CURRENT
    ## Reproducing Neural Discrete Representation Learning
### Course Project for IFT 6135 - Representation Learning
    COPY-PASTE FIX
    ## PyTorch Implementation of Vector Quantized Variational Autoencoders (VQ-VAE)
This repository provides a robust and efficient PyTorch implementation of the VQ-VAE model, originally developed for a course project on Neural Discrete Representation Learning.
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Set the repository's homepage URL in the 'About' section to `https://github.com/ritheshkumar95/pytorch-vqvae`.

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 ritheshkumar95/pytorch-vqvae
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
VQGAN
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. VQGAN · recommended 1×
  2. lucidrains/dalle-pytorch · recommended 1×
  3. VQ-VAE-2 · recommended 1×
  4. NÜWA · recommended 1×
  5. lucidrains/imagen-pytorch · recommended 1×
  • CATEGORY QUERY
    How can I generate high-quality images using discrete latent representations with PyTorch?
    you: not recommended
    AI recommended (in order):
    1. VQGAN
    2. DALL-E (lucidrains/dalle-pytorch)
    3. VQ-VAE-2
    4. NÜWA

    AI recommended 4 alternatives but never named ritheshkumar95/pytorch-vqvae. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a PyTorch implementation of vector quantized variational autoencoders for image data.
    you: not recommended
    AI recommended (in order):
    1. lucidrains/imagen-pytorch (lucidrains/imagen-pytorch)
    2. CompVis/latent-diffusion (CompVis/latent-diffusion)
    3. deepmind/sonnet (deepmind/sonnet)
    4. AntixK/PyTorch-VAE (AntixK/PyTorch-VAE)
    5. rosinality/vqvae-pytorch (rosinality/vqvae-pytorch)

    AI recommended 5 alternatives but never named ritheshkumar95/pytorch-vqvae. 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 ritheshkumar95/pytorch-vqvae?
    pass
    AI named ritheshkumar95/pytorch-vqvae explicitly

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

  • If a team adopts ritheshkumar95/pytorch-vqvae in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name ritheshkumar95/pytorch-vqvae — 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?

  • In one sentence, what problem does the repo ritheshkumar95/pytorch-vqvae solve, and who is the primary audience?
    pass
    AI did not name ritheshkumar95/pytorch-vqvae — 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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ritheshkumar95/pytorch-vqvae — 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
ritheshkumar95/pytorch-vqvae — RepoGEO report