Comments (4)
Hey! To run on CPU, you don't need to actually set the n_gpu
parameter yourself, it should default to 1 (and then ignore it) or 0... Have you tried this and ran into any issue?
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Hey! To run on CPU, you don't need to actually set the
n_gpu
parameter yourself, it should default to 1 (and then ignore it) or 0... Have you tried this and ran into any issue?
Hi @bclavie. I've tried using -1, 0, 1 but nothing seems to work. It keeps loading the model and index to my GPU RAM.
It should be mentioned that till now I had used GPU to run indexing flawlessly. To complete my project I now need to run an LLM model which leaves barely any VRAM on my GPU to run the retriever model and the Index.
I have my conda ragatouille environment setup to utilize the GPU packages. That's why i was wondering if there was any parameter i could change to force the retriever and index to run on using my CPU.
Thanks.
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Oh my bad, I was under the impression that you wee on a GPU-less machine!
I think the easiest way to get the retriever to not use the GPU at all would be to hide it from the script. Are you running it in a way where it's easy for you to set CUDA_VISIBLE_DEVICES=""
and/or tell torch to ignore it? There is room for change here but colbert-ai
still has a lot of hardcoded .cuda()
calls :/
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Thanks. I'll try setting CUDA_VISIBLE_DEVICES=""
and look into the torch thing. Will update here if i can do something.
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