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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| README.md | 2025-07-09 | 3.8 kB | |
| Release v1.0.17 source code.tar.gz | 2025-07-09 | 3.1 MB | |
| Release v1.0.17 source code.zip | 2025-07-09 | 3.4 MB | |
| Totals: 3 Items | 6.5 MB | 0 | |
July 7, 2025
- MobileNet-v5 backbone tweaks for improved Google Gemma 3n behaviour (to pair with updated official weights)
- Add stem bias (zero'd in updated weights, compat break with old weights)
- GELU -> GELU (tanh approx). A minor change to be closer to JAX
- Add two arguments to layer-decay support, a min scale clamp and 'no optimization' scale threshold
- Add 'Fp32' LayerNorm, RMSNorm, SimpleNorm variants that can be enabled to force computation of norm in float32
- Some typing, argument cleanup for norm, norm+act layers done with above
- Support Naver ROPE-ViT (https://github.com/naver-ai/rope-vit) in
eva.py, add RotaryEmbeddingMixed module for mixed mode, weights on HuggingFace Hub
| model | img_size | top1 | top5 | param_count |
|---|---|---|---|---|
| vit_large_patch16_rope_mixed_ape_224.naver_in1k | 224 | 84.84 | 97.122 | 304.4 |
| vit_large_patch16_rope_mixed_224.naver_in1k | 224 | 84.828 | 97.116 | 304.2 |
| vit_large_patch16_rope_ape_224.naver_in1k | 224 | 84.65 | 97.154 | 304.37 |
| vit_large_patch16_rope_224.naver_in1k | 224 | 84.648 | 97.122 | 304.17 |
| vit_base_patch16_rope_mixed_ape_224.naver_in1k | 224 | 83.894 | 96.754 | 86.59 |
| vit_base_patch16_rope_mixed_224.naver_in1k | 224 | 83.804 | 96.712 | 86.44 |
| vit_base_patch16_rope_ape_224.naver_in1k | 224 | 83.782 | 96.61 | 86.59 |
| vit_base_patch16_rope_224.naver_in1k | 224 | 83.718 | 96.672 | 86.43 |
| vit_small_patch16_rope_224.naver_in1k | 224 | 81.23 | 95.022 | 21.98 |
| vit_small_patch16_rope_mixed_224.naver_in1k | 224 | 81.216 | 95.022 | 21.99 |
| vit_small_patch16_rope_ape_224.naver_in1k | 224 | 81.004 | 95.016 | 22.06 |
| vit_small_patch16_rope_mixed_ape_224.naver_in1k | 224 | 80.986 | 94.976 | 22.06 |
| * Some cleanup of ROPE modules, helpers, and FX tracing leaf registration | ||||
| * Preparing version 1.0.17 release |
What's Changed
- Adding Naver rope-vit compatibility to EVA ViT by @rwightman in https://github.com/huggingface/pytorch-image-models/pull/2529
- Update no_grad usage to inference_mode if possible by @GuillaumeErhard in https://github.com/huggingface/pytorch-image-models/pull/2534
- Add a min layer-decay scale clamp, and no optimization threshold to exclude groups from optimization by @rwightman in https://github.com/huggingface/pytorch-image-models/pull/2537
- Add stem_bias option to MNV5. Resolve the norm layer so can pass string. by @rwightman in https://github.com/huggingface/pytorch-image-models/pull/2538
- Add flag to enable float32 computation for normalization (norm + affine) by @rwightman in https://github.com/huggingface/pytorch-image-models/pull/2536
- fix: mnv5 conv_stem bias and GELU with approximate=tanh by @RyanMullins in https://github.com/huggingface/pytorch-image-models/pull/2533
- Fixup casting issues for weights/bias in fp32 norm layers by @rwightman in https://github.com/huggingface/pytorch-image-models/pull/2539
- Fix H, W ordering for xy indexing in ROPE by @rwightman in https://github.com/huggingface/pytorch-image-models/pull/2541
- Fix 3 typos in README.md by @robin-ede in https://github.com/huggingface/pytorch-image-models/pull/2544
New Contributors
- @GuillaumeErhard made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2534
- @RyanMullins made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2533
- @robin-ede made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2544
Full Changelog: https://github.com/huggingface/pytorch-image-models/compare/v1.0.16...v1.0.17