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Instead of doing the tensor conversion manually, we can do something like
dataset.set_format(type='torch', columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
as shown in datasets doc. This would also enable removing the unused columns (the columns not required by the models) conveniently.
The text was updated successfully, but these errors were encountered:
Instead of doing the tensor conversion manually, we can do something like
dataset.set_format(type='torch', columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
as shown in datasets doc. This would also enable removing the unused columns (the columns not required by the models) conveniently.
The text was updated successfully, but these errors were encountered: