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Optimized Stable Diffusion modified to run on lower GPU VRAM

28 mentions on Hacker News by 23 people: 1 story, 27 comments · first 2022-08-22 · latest 2022-09-19

Mentions per year 28 mentions · busiest year 2022 (28)
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  1. There is a fork at https://github.com/basujindal/stable-diffusion which is optimized for 8gb cards, I have been using it to run SD on my 8gb 1080 That fork released around when SD released, I've been wondering if anyone's integrated those…
  2. …container that seems to have disappeared, this modified version for amd cards with less than 10gb: https://github.com/basujindal/stable-diffusion and this workaround: https://github.com/RadeonOpenCompute/ROCm/issues/1756#issuec... Anyway,…
  3. Try the basujindal fork https://github.com/basujindal/stable-diffusion - this is what works for me on 8gb of VRAM (without maybe 6.5 available from whatever my DE is using up). On Linux with AMD `radeontop` is quite informative.
  4. …https://github.com/awesome-stable-diffusion/awesome-stable-d... to "Optimized Stable Diffusion" https://github.com/basujindal/stable-diffusion (linked many times in this discussion).
  5. Use halfprecision float and/or the optimized forks https://github.com/basujindal/stable-diffusion https://github.com/neonsecret/stable-diffusion Or the hlky webui, that is optimized too. http://rentry.co/kretard
  6. Also there are two optimized forks which run on < 6 GB https://github.com/basujindal/stable-diffusion https://github.com/neonsecret/stable-diffusion
  7. The diff that apparently does the RAM optimisation, quite simple and something to learn form: https://github.com/basujindal/stable-diffusion/commit/47f878...
  8. …and significantly reduce memory requirements. I'd expect slightly worse results, though. edit: also https://github.com/basujindal/stable-diffusion/pull/103
  9. https://github.com/basujindal/stable-diffusion I use this on my Ubuntu 18 machine, works nicely on a GPU with 8GB VRAM. As usual, some python dependency nonsense to sort out even with Anaconda, but pretty quick and easy to get up and…
  10. …changes. (More work, and coordination, but each PR is "one unit of work") - Better commit messages: https://github.com/basujindal/stable-diffusion/pull/103#comm... <- notice the repeated and non-descript commit messages? That makes it hard…
  11. …with as little as 4GB VRAM. [0] https://github.com/CompVis/stable-diffusion#stable-diffusion [1] https://github.com/basujindal/stable-diffusion#txt2img
  12. …It seems the only changeset that might be relevant out of +2,273 -1,531 is the +11 -7 from https://github.com/basujindal/stable-diffusion/pull/103/comm... ? Does it even work?
  13. …author of this PR decided to include garbage like this [1] in it, so this PR is pretty useless. [1] https://github.com/basujindal/stable-diffusion/pull/103/file...
  14. can run with gui: https://github.com/basujindal/stable-diffusion/blob/main/opt...
  15. I tried to run locally but all I got is a black square for output. I used the scripts from this Repo https://github.com/basujindal/stable-diffusion which didn't give me a GPU memory error which the original link does.
  16. …similar generation time to the low vram fork of stable diffusion [1] running on my 4GB GTX1650. [1] https://github.com/basujindal/stable-diffusion
    comment by neurostimulant · 2022-08-31 · in Run Stable Diffusion on Intel CPUs
  17. …[0]: https://github.com/lstein/stable-diffusion [1]: https://github.com/hlky/stable-diffusion [2]: https://github.com/basujindal/stable-diffusion
  18. …standard model, but ran into OOM issues. I don't mind waiting, so now I am using the "fast" repo: https://github.com/basujindal/stable-diffusion With this, it takes 30s to generate a 768x512 image (any larger and I am experiencing OOM…
    comment by mlsu · 2022-08-30 · in 1 week of Stable Diffusion
  19. I'm using the fork at https://github.com/basujindal/stable-diffusion which is optimized for lower VRAM usage. My RTX 2070 (8 GB) takes about 90 seconds to generate a batch of 4 images.
    comment by orangecat · 2022-08-30 · in 1 week of Stable Diffusion
  20. …[0]: https://github.com/lstein/stable-diffusion [1]: https://github.com/hlky/stable-diffusion [2]: https://github.com/basujindal/stable-diffusion
    comment by cube2222 · 2022-08-30 · in 1 week of Stable Diffusion
  21. …cuda and python-pytorch-opt-cuda; all the relevant Arch packages came to about 14GB). I’m using https://github.com/basujindal/stable-diffusion to run it since I only have 6GB of VRAM. I’m having fun. But I haven’t had much luck getting it…
  22. …instructions from the readme for some reason. The requirements section can be found in this diff: https://github.com/basujindal/stable-diffusion/commit/487a0f...
  23. …also a fork that requires a lot less VRAM. I was able to get this working with an Nvidia GTX 1070. https://github.com/basujindal/stable-diffusion You'd clone the fork, then download Stability AI's checkpoint, sd-v1-4.ckpt, from…
  24. If you have a GPU that has more than 4 GB VRAM, you should be able to easily run it: https://github.com/basujindal/stable-diffusion I didn't manage to run it on mine, as it segfaults, but I've heard of people running it fine on an old 1060…
    comment by stavros · 2022-08-24 · in Mainnet Merge Announcement
  25. I used the optimized script from https://github.com/basujindal/stable-diffusion , I think it does that automatically?
    comment by stavros · 2022-08-23 · in Stable Diffusion Public Release
  26. …| ID | GPU | MEM | ------------------ | 0 | 1% | 6% | Edit 2: Got this optimized fork to work: https://github.com/basujindal/stable-diffusion
    comment by entrep · 2022-08-22 · in Stable Diffusion Public Release
  27. There's a version that's a bit slower but more memory efficient https://github.com/basujindal/stable-diffusion that runs on 6GB too.
    comment by ompto · 2022-08-22 · in Stable Diffusion Public Release