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I'm bound by the collab gpu limit so for it not to crash I can only use a part of my data. When I try to run the training again on the ludwig adapter it gives this weird error:
Output :
<ipython-input-65-c315fad6269b> in <cell line: 1>()
----> 1 results = model.train(df)
14 frames
/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py in __getattr__(self, name)
1693 if name in modules:
1694 return modules[name]
-> 1695 raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
1696
1697 def __setattr__(self, name: str, value: Union[Tensor, 'Module']) -> None:
AttributeError: 'Linear4bit' object has no attribute 'compute_dtype'
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I'm bound by the collab gpu limit so for it not to crash I can only use a part of my data. When I try to run the training again on the ludwig adapter it gives this weird error:
Any ideas to bypass this?
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