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taming-transformers
Jupyter Notebook2021–2021
CompVis / taming-transformers

taming-transformers

Taming Transformers for High-Resolution Image Synthesis

2Distinct people
3Mentions
0Explicit recommenders
6.5KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Taming Transformers for High-Resolution Image Synthesis

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 2:59:58 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week3 dated mentions

Observed mentions: 2021-07-02 14:44:41 UTC to 2021-10-03 19:39:13 UTC. Weeks start Monday, UTC.

0122021-06-28 00:00:00 UTC to 2021-07-05 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsJun 282021-07-05 00:00:00 UTC to 2021-07-12 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-07-12 00:00:00 UTC to 2021-07-19 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-07-19 00:00:00 UTC to 2021-07-26 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-07-26 00:00:00 UTC to 2021-08-02 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-02 00:00:00 UTC to 2021-08-09 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-09 00:00:00 UTC to 2021-08-16 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsAug 92021-08-16 00:00:00 UTC to 2021-08-23 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-23 00:00:00 UTC to 2021-08-30 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-08-30 00:00:00 UTC to 2021-09-06 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-09-06 00:00:00 UTC to 2021-09-13 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-09-13 00:00:00 UTC to 2021-09-20 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-09-20 00:00:00 UTC to 2021-09-27 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-09-27 00:00:00 UTC to 2021-10-04 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 27

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jun 282021-06-28 00:00:00 UTC2021-07-05 00:00:00 UTC202
Jul 52021-07-05 00:00:00 UTC2021-07-12 00:00:00 UTC000
Jul 122021-07-12 00:00:00 UTC2021-07-19 00:00:00 UTC000
Jul 192021-07-19 00:00:00 UTC2021-07-26 00:00:00 UTC000
Jul 262021-07-26 00:00:00 UTC2021-08-02 00:00:00 UTC000
Aug 22021-08-02 00:00:00 UTC2021-08-09 00:00:00 UTC000
Aug 92021-08-09 00:00:00 UTC2021-08-16 00:00:00 UTC000
Aug 162021-08-16 00:00:00 UTC2021-08-23 00:00:00 UTC000
Aug 232021-08-23 00:00:00 UTC2021-08-30 00:00:00 UTC000
Aug 302021-08-30 00:00:00 UTC2021-09-06 00:00:00 UTC000
Sep 62021-09-06 00:00:00 UTC2021-09-13 00:00:00 UTC000
Sep 132021-09-13 00:00:00 UTC2021-09-20 00:00:00 UTC000
Sep 202021-09-20 00:00:00 UTC2021-09-27 00:00:00 UTC000
Sep 272021-09-27 00:00:00 UTC2021-10-04 00:00:00 UTC101

What Hacker News says

1 sources
What sort of compute do you get access to? There's a lot of cool stuff you could do depending on whether or not you have decent GPU's and for how much time you're allowed to experiment on them. Experimentation is fairly fundamental in practice. There are a lot of pretraining tasks in vision/multimodal that are cool. Largely techniques introduced or refined by OpenAI re-implemented as pytorch open source codebases with varying degrees of success: - Finetune your own CLIP https://github.com/mlfoundations/open_clip - Train a (much smaller) DALLE https://github.com/lucidrains/DALLE-pytorch - Train your own guided diffusion https://colab.research.google.com/drive/1javQRTkALBWLFWnx1K4... (pretty tough, may only be feasible on domain-specific data) - Train a variational autoencoder (VAE) - "VQGAN" from Heidelberg https://github.com/CompVis/tamin
Read the rest
g-transformers - "Discrete VAE", used as the backbone for OpenAI's DALL-E, reimplimented here (and other places) https://github.com/lucidrains/DALLE-pytorch - "VQVAE2" https://github.com/tgisaturday/dalle-lightning
In Ask HN: Computer Vision Project Ideas?

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