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I am trying to follow the instructions for bark from the HuggingFace Bark Docs and I saw the part where it said that I can reduce memory footprint by running in half precision by doing the following:
model = BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float16).to('cpu')
However when I do this, it crashes with the following error:
In model = BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float16).to('cpu'), you are setting the dtata type to a half float try loading it in full float model = BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float32).to('cpu').
I am trying to follow the instructions for bark from the HuggingFace Bark Docs and I saw the part where it said that I can reduce memory footprint by running in half precision by doing the following:
model = BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float16).to('cpu')
However when I do this, it crashes with the following error:
What is causing this? Is there something else I need to add to my code?
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