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From your paper and blog post, the quantization was tested using transformers. Is it possible to use the library for objet detection models and will it experience performance degradation?
The text was updated successfully, but these errors were encountered:
I have not tested this, but it should be possible for vision transformers. I known already from data that vision transformers behave the very same in terms of outliers than language model transformers. As such, I think it will work.
However, it will not straightforwardly work for convolutional networks, since the current implementation just supports the replacement of torch.nn.Linear layers and not convolutional layers with the 8-bit equivalent.
From your paper and blog post, the quantization was tested using transformers. Is it possible to use the library for objet detection models and will it experience performance degradation?
The text was updated successfully, but these errors were encountered: