transformers
bc9ecef9 - Use new parametrization based weight norm if available (#24030)

Commit

3 years ago

Use new parametrization based weight norm if available (#24030) * Use new parametrization based weight norm if available See https://github.com/pytorch/pytorch/pull/103001 Signed-off-by: Edward Z. Yang <ezyang@meta.com> * handle copies Signed-off-by: Edward Z. Yang <ezyang@meta.com> * black Signed-off-by: Edward Z. Yang <ezyang@meta.com> --------- Signed-off-by: Edward Z. Yang <ezyang@meta.com>

References

#24030 - Use new parametrization based weight norm if available

#27720 - Add common processor tests

#29969 - [SigLIP] Add fast tokenizer

#32831 - [Docs] Update resources

#33111 - [Backbone] Remove out_features everywhere

#33174 - [Zero-shot image classification pipeline] Remove tokenizer_kwargs

#59 - Fix attention mask handling in EoMT-DINOv3 converter

#62 - Add initial DEIMv2 model implementation

#65 - Fix RTDetrV2 sine position embedding ordering

#44375 - Add RF-DETR

#71 - Use Mask2Former ignore_value in mask matching and losses