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There are forks that even work on 1.8 of VRAM! They work great on my GTX 1050 2GB. This is by far the most popular and active right now: https://github.com/AUT

• jaggs 4y ago
  This needs Windows 10/11 though?
  • Karuma 4y ago
    Nope. There are instructions for Windows, Linux and Apple Silicon in the readme: https://github.com/AUTOMATIC1111/stable-diffusion-webui https://github.com/AUTOMATIC1111/stable-diffusion-webui There's also this fork of AUTOMATIC1111's fork, which also has a Colab notebook ready to run, and it's way, way faster than the KerasCV version: https://github.com/TheLastBen/fast-stable-diffusion https://github.com/TheLastBen/fast-stable-diffusion (It also has many, many more options and some nice, user-friendly GUIs. It's the best version for Google Colab!)
    • jaggs 4y ago
      Brilliant thanks.
• deleted 4y ago
  [deleted]
• sophrocyne 4y ago
  While AUTOMATIC is certainly popular, calling it the most active/popular would be ignoring the community working on Invoke. Forks don’t lie. https://github.com/invoke-ai/InvokeAI https://github.com/invoke-ai/InvokeAI
  • counttheforks 4y ago
    > Forks don’t lie. They sure do. InvokeAI is a fork of the original repo CompVis/stable-diffusion and thus shares its fork counter. Those 4.1k forks are coming from CompVis/stable-diffusion, not InvokeAI. Meanwhile AUTOMATIC1111/stable-diffusion-webui is not a fork itself, and has 511 forks.
    • pwillia7 4y ago
      Subjectively, AUTOMATIC has taken over -- I have not heard of invoke yet but will check it out.
      • toqy 4y ago
        The only reason to use it imo has been if you need mac/m1 support, but that's probably in other forks by now
    • sophrocyne 4y ago
      Welp - TIL. Thanks for the correction. Any idea on how to count forks of a downstream fork? If anyone would know... :)
• rmurri 4y ago
  What settings and repo are you using for GTX 1050 with 2GB?
  • Karuma 4y ago
    I'm using the one I linked in my original post: https://github.com/AUTOMATIC1111/stable-diffusion-webui https://github.com/AUTOMATIC1111/stable-diffusion-webui The only command line argument I'm using is --lowvram, and usually generate pictures at the default settings at 512x512 image size. You can see all the command line arguments and what they do here: https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Run-with-Custom-Parameters https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...
• jtap 4y ago
  Just as another point of reference. I followed the windows install. I'm running this on my 1060 with 6GB memory. With no setting changes takes about 10 seconds to generate an image. I often run with sampling steps up to 50 and that takes about 40 seconds to generate an image.
• extesy 4y ago
  > This is by far the most popular and active right now: https://github.com/AUTOMATIC1111/stable-diffusion-webui https://github.com/AUTOMATIC1111/stable-diffusion-webui While technically the most popular, I wouldn't call it "by far". This one is a very close second (500 vs 580 forks): https://github.com/sd-webui/stable-diffusion-webui/tree/dev https://github.com/sd-webui/stable-diffusion-webui/tree/dev
  • Karuma 4y ago
    That's why I said "right now", since I feel that most people have moved from the one you linked to AUTOMATIC's fork by now. hlky's fork (the one you linked) was by far the most popular one until a couple of weeks ago, but some problems with the main developer's attitude and a never-ending migration from Gradio to Streamlit filled with issues made it lose its popularity. AUTOMATIC has the attention of most devs nowadays. When you see any new ideas come up, they usually appear in AUTOMATIC's fork first.
• Abishek_Muthian 4y ago
  I guess then it could even work on a Jetson Nano(4GB) then, I run models of ~1.6 GB on it 24*7; Would give this a try.