Use Multiple GPUs with InternVL2

[Backendmagier]

Is it possible to use multiple GPUs? im having 2 3090s but i cant get InternVL26B to run as it is always running on only one Card...

I try to start it like this: "CUDA_VISIBLE_DEVICES=1,0 python vision.py --model OpenGVLab/InternVL2-26B --device-map sequential"

and i get this error: "torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 32.00 MiB. GPU 1 has a total capacity of 23.55 GiB of which 9.19 MiB is free. Including non-PyTorch memory, this process has 23.52 GiB memory in use. Of the allocated memory 23.02 GiB is allocated by PyTorch, and 125.25 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)"

[matatonic]

Not yet, but there has been an update by the model maker indicating how to do this, I will update it in an upcoming release.

[Backendmagier]

alright, thank you!

[matatonic]

(I'll close the issue when it's fixed)

[AlexM4H]

BTW: Hint from the model maker https://huggingface.co/OpenGVLab/InternVL2-40B/blob/main/README.md#multiple-gpus