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huggingface
diffusers
Python2022–2024
huggingface / diffusers

diffusers

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

AI & Machine LearningCreative & MediaLearning & Reference
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20Distinct people
32Mentions
1Explicit recommenders
34.9KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

I've been using the HuggingFace diffuses repo[1] with 6GB of VRAM fine. It's well engineered, maintainable and with decent installation process. The branch in this PR[2] adds…

nl used a recommendation phrase. One indexed comment matches. This is a phrase match, not a verdict.

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

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 7:56:55 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 month32 dated mentions

Observed mentions: 2022-07-21 16:41:11 UTC to 2024-10-16 08:36:47 UTC.

02468102022-07-01 00:00:00 UTC to 2022-08-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsJul 20222022-08-01 00:00:00 UTC to 2022-09-01 00:00:00 UTC (exclusive): 7 mentions; 2 submissions, 5 comments2022-09-01 00:00:00 UTC to 2022-10-01 00:00:00 UTC (exclusive): 10 mentions; 0 submissions, 10 comments2022-10-01 00:00:00 UTC to 2022-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-11-01 00:00:00 UTC to 2022-12-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2022-12-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-01-01 00:00:00 UTC to 2023-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-02-01 00:00:00 UTC to 2023-03-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-03-01 00:00:00 UTC to 2023-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-04-01 00:00:00 UTC to 2023-05-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsAug 20232023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 2024

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
Jul 20222022-07-01 00:00:00 UTC2022-08-01 00:00:00 UTC110
Aug 20222022-08-01 00:00:00 UTC2022-09-01 00:00:00 UTC725
Sep 20222022-09-01 00:00:00 UTC2022-10-01 00:00:00 UTC10010
Oct 20222022-10-01 00:00:00 UTC2022-11-01 00:00:00 UTC000
Nov 20222022-11-01 00:00:00 UTC2022-12-01 00:00:00 UTC110
Dec 20222022-12-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
Jan 20232023-01-01 00:00:00 UTC2023-02-01 00:00:00 UTC000
Feb 20232023-02-01 00:00:00 UTC2023-03-01 00:00:00 UTC101
Mar 20232023-03-01 00:00:00 UTC2023-04-01 00:00:00 UTC101
Apr 20232023-04-01 00:00:00 UTC2023-05-01 00:00:00 UTC110
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC000
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC000
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC101
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC101
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC000
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC202
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC110
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC000
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC000
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC000
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC000
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC303
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC000
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC000
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC000
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC000
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC101

What Hacker News says

10 sources
montebicyclelo¡Sep 19, 2022
You can 100% run this on an 8gb card. Make sure to load the model weights in half precision (and optionally enable attention slicing). E.g., using the diffusers library [1]: from diffusers import StableDiffusionPipeline from torch import autocast pipe = StableDiffusionPipeline.from_pretrained( "CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16, use_auth_token=True ) pipe = pipe.to("cuda") pipe.enable_attention_slicing() prompt = "a photo of an astronaut riding a horse on mars" with autocast("cuda"): image = pipe(prompt).images[0] [1] https://github.com/huggingface/diffusers
In I Resurrected “Ugly Sonic” with Stable Diffusion Textual Inversion
nl¡Sep 12, 2022
I don't understand why all these crazy forks don't switch to using the HuggingFace codebase[1]. It's much better code and easier to add features to. It's true you have to use the code from git rather than a release, but that's not hard. https://github.com/nlothian/m1_huggingface_diffusers_demo is my clean demo repo with a notebook showing the usage. The standard HuggingFace examples (eg for img2img[2]) port across with no trouble too. [1] https://github.com/huggingface/diffusers [2] https://github.com/huggingface/diffusers#image-to-image-text...
In Diffusion Bee: Stable Diffusion GUI App for M1 Mac
JimDabell¡Sep 4, 2022
I wouldn’t recommend using that as-is. MPS doesn’t give deterministic random number generation, which means that seeds become meaningless and you won’t ever be able to reproduce something. You can work around it by generating random numbers on the CPU and then moving them to MPS, but that probably requires a fix in PyTorch. The MPS support issue for diffusers is here: https://github.com/huggingface/diffusers/issues/292 …and it links to the relevant PyTorch issue here: https://github.com/pytorch/pytorch/issues/84288
In Stable Diffusion PR optimizes VRAM, generate 576x1280 images with 6 GB VRAM
nl¡Sep 4, 2022Recommendation phrase
I've been using the HuggingFace diffuses repo[1] with 6GB of VRAM fine. It's well engineered, maintainable and with decent installation process. The branch in this PR[2] adds M1 Mac support with a one line patch and it runs faster than the CompVis version (1.5 iterations/sec vs 1.4 for CompVis on a 32 Gb M1 Max, I highly recommend people switching to that version for the improved flexibility. [1] https://github.com/huggingface/diffusers [2] https://github.com/huggingface/diffusers/pull/278
In Stable Diffusion PR optimizes VRAM, generate 576x1280 images with 6 GB VRAM

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