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Can you train on it too? I tried Pytorch on AMD once and it was awful. They promised mountains but delivered nothing. Newer activation functions were all broken.
llama.cpp is inference only, for which AMD works great too after converting to ONNX. But training was awful on AMD in the past.
It takes a long time for large companies to change their purchases. Many of these datacenter contracts are locked in for years. You can’t just change them overnight.
You can train or fine-tune a model on any GPU. Surely, It will be slower, but higher VRAM is better.
No. The CUDA training stuff is Nvidia only.
Pytorch runs on HIP now.
AMD has been lying about that every year since 2019.
Last time I checked it didn’t. And it probably still doesn’t.
People aren’t buying NVIDIA if AMD would work too. The VRAM prices NVIDIA asks are outrageous.
I run llama.cpp and PyTorch on MI300s. It works really well.
Can you train on it too? I tried Pytorch on AMD once and it was awful. They promised mountains but delivered nothing. Newer activation functions were all broken.
llama.cpp is inference only, for which AMD works great too after converting to ONNX. But training was awful on AMD in the past.
We have trained transformers and diffusion models on AMD MI300s, yes.
Interesting. So why does NVIDIA still hold such a massive monopoly on the datacenter?
It takes a long time for large companies to change their purchases. Many of these datacenter contracts are locked in for years. You can’t just change them overnight.