StableDiffusion

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The original was posted on /r/stablediffusion by /u/eggs-benedryl on 2024-08-21 00:12:02+00:00.

Like 10 people have model pages all with 5 or so models each all with different acronyms...

Not keeping up with it all for just a few days I'm so far behind already.

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The original was posted on /r/stablediffusion by /u/setothegreat on 2024-08-21 04:26:34+00:00.

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The original was posted on /r/stablediffusion by /u/Altruistic_Gibbon907 on 2024-08-20 22:35:21+00:00.

Luma AI new update to its Dream Machine text-to-video generator, version 1.5, adds enhanced realism, improved motion tracking, and smarter understanding of prompts.

• Can now render text within generated videos, for dynamic title sequences, animated logos, and on-screen graphics
• Improved handling of non-English prompts
• 5x speed boost, generating 5 seconds of high-quality video in 2 minutes

Source: Luma AI

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The original was posted on /r/stablediffusion by /u/lewdstoryart on 2024-08-20 21:26:15+00:00.

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The original was posted on /r/stablediffusion by /u/westedmontonballs on 2024-08-21 00:13:34+00:00.

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The original was posted on /r/stablediffusion by /u/Kawamizoo on 2024-08-20 22:11:51+00:00.

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The original was posted on /r/stablediffusion by /u/Jeremy8776 on 2024-08-20 20:07:57+00:00.

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The original was posted on /r/stablediffusion by /u/Striking-Long-2960 on 2024-08-20 19:41:09+00:00.

It seems it has happened again. I'm not going to discuss whether the generated pictures are better or worse, but including 'art by Greg Rutkowski' can have a significant impact on the images, making them darker and more detailed.

photography, an alien monster eating a burger

photography, an alien monster eating a burger. art by Greg Rutkowski.

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The original was posted on /r/stablediffusion by /u/ApatheticJackal on 2024-08-20 18:39:31+00:00.

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The original was posted on /r/stablediffusion by /u/appenz on 2024-08-20 17:57:14+00:00.

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The original was posted on /r/stablediffusion by /u/Agreeable_Gap_5927 on 2024-08-20 20:30:00+00:00.

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The original was posted on /r/stablediffusion by /u/rerri on 2024-08-20 18:51:57+00:00.

Works with FP8e4m3fn only, argument: --fast

Need torch 2.4.0, so update using update_comfyui_and_python_dependencies.bat if you wanna try.

Went from 14sec -> 10sec per image, 1024x1024, 20steps.

2.5 GHz at 875mV:

100%|█████████████████████████████████| 20/20 [00:10<00:00, 1.87it/s]

2.8 GHz almost getting to 2it/s:

100%|█████████████████████████████████| 20/20 [00:10<00:00, 1.98it/s]

PS. Image quality is different with --fast than without it. I'm not sure if the change is for the better, worse, neither. Only just trying this.

edit: LoRA's work, Schnell works, can use GGUF for T5.

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The original was posted on /r/stablediffusion by /u/skyyguy1999 on 2024-08-20 17:33:44+00:00.

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The original was posted on /r/stablediffusion by /u/Agreeable_Effect938 on 2024-08-20 17:03:04+00:00.

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The original was posted on /r/stablediffusion by /u/morerice4u on 2024-08-20 15:49:51+00:00.

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The original was posted on /r/stablediffusion by /u/Takeacoin on 2024-08-20 11:47:50+00:00.

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The original was posted on /r/stablediffusion by /u/PandaWhelp on 2024-08-20 09:30:31+00:00.

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The original was posted on /r/stablediffusion by /u/Christianman88 on 2024-08-20 14:06:38+00:00.

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The original was posted on /r/stablediffusion by /u/Droploris on 2024-08-20 13:12:51+00:00.

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The original was posted on /r/stablediffusion by /u/cene6555 on 2024-08-20 10:01:02+00:00.

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The original was posted on /r/stablediffusion by /u/Naetharu on 2024-08-20 08:06:34+00:00.

I thought I would share this as I’ve not seen it mentioned elsewhere. I’m working with Flux at the moment, but I wanted to save some of my VRAM for other uses. So I made a manual edit to the Comfy UI code to cap my VRAM below the actual card limit.

The results are interesting.

I have an RTX4090 with 24GB of VRAM and 64GB of system RAM.

Without the changes I can create a 800 x 1200 image in 20 steps in ~17 seconds. As I reduce the VRAM the speed of generations increases as you might expect. But nowhere near as much as I had anticipated.

At 12GB of VRAM allocation I get 1.8s/it for a generation of around 35 seconds.

And most interesting I can take this all the way down to just 3GB of VRAM, and still get 2.3s/it for a generation of around 44 seconds in total. This also reduces the load on the GPU way down to around 50% for the 4090.

This allows me to run other GPU based software (a local LLM in my case) at the same time. It also allows me to run flux image generation in the background while playing some games.

I’m going to put the information together and make a proposal for adding this as an official option in the UI later. But for now I thought it might be helpful to some others here.

Another note is that hard-coding the limit this way seems to result in better performance and less OOM errors than allowing the official calculation to do the work. So if you have a lower end GPU it might be worth trying to set the memory this way (you can google bits in a GB to find your optimal numbers) and testing to see if you get more consistent and faster generations.

The code you need to change is:

1: Line 520 in model_management.py (this sets the lowvram limit for the first load)

2: Line 680 in model_patcher.py (this sets the lowvram limit for subsiquent runs)

You can create git branches for the different VRAM configurations so you can easily swap between them before loading Comfy.

EDIT: I just thought I would add that I am using the Nvidia Studio Ready Drivers - I have no idea if this makes any difference, but worth mentioning as I assume many folk may be using the Game Ready drivers. If you do want to install the SRD you can do so via GForce Experience, by going to drivers, and then into the pips option. In theory the SRD is better optimized for studio work such as AI generations and video editing. I've not yet tested this with the game drivers.

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The original was posted on /r/stablediffusion by /u/Late_Lingonberry6252 on 2024-08-20 07:58:00+00:00.

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The original was posted on /r/stablediffusion by /u/Storybook_Tobi on 2024-08-20 09:34:11+00:00.

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The original was posted on /r/stablediffusion by /u/OkSpot3819 on 2024-08-20 08:53:53+00:00.

• Low VRAM Flux: New technique allows running Flux on GPUs with as little as 3-4GB of VRAM.
• GGUF quantization: Successfully applied to Flux, offering significant model compression with minimal quality loss.
• NF4 Flux v2: Refined version with improved quantization, higher precision, and reduced computational overhead.
• Union controlnet: Alpha version released for FLUX.1 dev model, combining multiple control modes.
• X-Labs LoRAs: Six new FLUX.1-dev style adaptation models released under non-commercial license.
• Civitai Flux LoRA training: Now available on the platform, with Kohya and X-Flux engine options.
• FLUXRealisticV1: New checkpoint trained on 7,000+ images for more diverse and realistic output.
• AI in Filmmaking: SIGGRAPH 2024 experts discuss AI's current limitations and future potential in cinema.
• X's Unrestricted AI Image Generator: New Grok chatbot feature for Premium subscribers sparks debate over content moderation.
• VFusion3D: Meta's new method for 3D asset generation from a single image.
• Google's Imagen 3: Advanced text-to-image AI model claiming to outperform DALL-E 3 and Midjourney V6.
• "Manual" App: Open-source UI released for ComfyUI.
• SimpleTuner v0.9.8.1: Enhanced tool for AI model fine-tuning, especially for Flux-dev models.
• New Flux LoRAs: RPG v6, Flat Color Anime v3.1, Aesthetic LoRA, and Impressionist Landscape released.
• AuraFlow-v0.3: New release available on Hugging Face.

Click here to read the full newsletter with proper formatting, links, visuals, etc.

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The original was posted on /r/stablediffusion by /u/Iory1998 on 2024-08-20 01:18:40+00:00.