Comment by sieve
9 hours ago
If you want to train/sample large models, then use what the rest of the industry uses.
My use case is different. I want something that I can run quickly on one GPU without worrying about whether it is supported or not.
I am interested in convenience, not in squeezing out the last bit of performance from a card.
You wildly misunderstand pytorch.
What is there to misunderstand? It doesn't even install properly most of the time on my machine. You have to use a specific python version.
I gave up on all tools that depend on it for inference. llama-cpp compiles cleanly on my system for Vulkan. I want the same simplicity to test model training.
pytorch is as easy as you are going to find for your exact use case. If you can't handle the requirement of a specific version of python, you are going to struggle in software land. ChatGPT can show you the way.
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I suspect the OP's issues might be mostly related to the ROCM version of PyTorch. AMD still can't get this right.
Probably - but the answer is to avoid ROCM, not pytorch.