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currently, we use pretty much float32 tensors all around, which yields pretty huge models.
after discussion with @martinjaggi, training is hard to do without float32, but inference can probably utilize uint8 tensors, dividing up to 4x the size of trained models.
note: check that the model is still behaving correctly after quantization
The text was updated successfully, but these errors were encountered:
currently, we use pretty much float32 tensors all around, which yields pretty huge models.
after discussion with @martinjaggi, training is hard to do without float32, but inference can probably utilize uint8 tensors, dividing up to 4x the size of trained models.
note: check that the model is still behaving correctly after quantization
The text was updated successfully, but these errors were encountered: