Jan 5 & 6, 2025
- Patch Release 1.0.24 (fix for 1.0.23)
- Add new benchmark result csv files for inference timing on all models w/ RTX Pro 6000, 5090, and 4090 cards w/ PyTorch 2.9.1
- Fix moved module error in deprecated timm.models.layers import path that impacts legacy imports
- Release 1.0.23
Dec 30, 2025
- Add better NAdaMuon trained
dpwee, dwee, dlittle (differential) ViTs with a small boost over previous runs
- Add a ~21M param
timm variant of the CSATv2 model at 512x512 & 640x640
- Factor non-persistent param init out of
__init__ into a common method that can be externally called via init_non_persistent_buffers() after meta-device init.
Dec 12, 2025
- Add CSATV2 model (thanks https://github.com/gusdlf93) -- a lightweight but high res model with DCT stem & spatial attention. https://huggingface.co/Hyunil/CSATv2
- Add AdaMuon and NAdaMuon optimizer support to existing
timm Muon impl. Appears more competitive vs AdamW with familiar hparams for image tasks.
- End of year PR cleanup, merge aspects of several long open PR
- Merge differential attention (
DiffAttention), add corresponding DiffParallelScalingBlock (for ViT), train some wee vits
- Add a few pooling modules,
LsePlus and SimPool
- Cleanup, optimize
DropBlock2d (also add support to ByobNet based models)
- Bump unit tests to PyTorch 2.9.1 + Python 3.13 on upper end, lower still PyTorch 1.13 + Python 3.10
Dec 1, 2025
- Add lightweight task abstraction, add logits and feature distillation support to train script via new tasks.
- Remove old APEX AMP support
What's Changed
New Contributors
Full Changelog: https://github.com/huggingface/pytorch-image-models/compare/v1.0.22...v1.0.24