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For stable diffusion, I have found the DirectML fork works great (https://community.amd.com/t5/ai/how-to-automatic1111-stable-diffusion-webui-with-directml/ba-p
by FuriouslyAdrift 3y ago
For stable diffusion, I have found the DirectML fork works great (https://community.amd.com/t5/ai/how-to-automatic1111-stable-diffusion-webui-with-directml/ba-p/649027 https://community.amd.com/t5/ai/how-to-automatic1111-stable-...)
Needs a few start arguments (--lowvram --precision full --no-half --skip-torch-cuda-test). YMMV.
GPT4All also works well for LLML on AMD.
- tharmas 3y agoMany thanks for the reference to GPT4All. I wasn't aware of it before.
- blagie 3y agoKind of. Here's the basic problem: 1) The BIG tools have SOME port to AMD. I am confident that one can run Mistral or SD in some framework there. 2) It's a port. If you want to do anything bleeding edge, development, niche, or similar, it's a dumpster fire. I do dome amount of development which uses LLMs. I want to be able to use a model directly from Hugging Face and have it just work.
- FuriouslyAdrift 3y agoOnly reason I am using the DirectML fork of Automatic1111 is because I am on Windows and pytorch hasn't caught up to RocM 6. DirectML is fully supported path on Windows and is support by Microsoft et al. (https://github.com/microsoft/DirectML https://github.com/microsoft/DirectML). Everyone is moving off Cuda as quickly as possible not because the other are better, per se, but because it is easier and cheaper.