Update README.md

Author: rwightman

README.md

@@ -26,6 +26,31 @@
 * The Hugging Face Hub (https://huggingface.co/timm) is now the primary source for `timm` weights. Model cards include link to papers, original source, license. 
 * Previous 0.6.x can be cloned from [0.6.x](https://github.com/rwightman/pytorch-image-models/tree/0.6.x) branch or installed via pip with version.
 
+### May 11, 2024
+* `Searching for Better ViT Baselines (For the GPU Poor)` weights and vit variants released. Exploring model shapes between Tiny and Base.
+
+| model | top1 | top5 | param_count | img_size |
+| -------------------------------------------------- | ------ | ------ | ----------- | -------- |
+| [vit_mediumd_patch16_reg4_gap_256.sbb_in12k_ft_in1k](https://huggingface.co/timm/vit_mediumd_patch16_reg4_gap_256.sbb_in12k_ft_in1k) | 86.202 | 97.874 | 64.11 | 256 |
+| [vit_betwixt_patch16_reg4_gap_256.sbb_in12k_ft_in1k](https://huggingface.co/timm/vit_betwixt_patch16_reg4_gap_256.sbb_in12k_ft_in1k)  | 85.418 | 97.48 | 60.4 | 256 |
+| [vit_mediumd_patch16_rope_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_mediumd_patch16_rope_reg1_gap_256.sbb_in1k)  | 84.322 | 96.812 | 63.95 | 256 |
+| [vit_betwixt_patch16_rope_reg4_gap_256.sbb_in1k](https://huggingface.co/timm/vit_betwixt_patch16_rope_reg4_gap_256.sbb_in1k)  | 83.906 | 96.684 | 60.23 | 256 |
+| [vit_base_patch16_rope_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_base_patch16_rope_reg1_gap_256.sbb_in1k)  | 83.866 | 96.67 | 86.43 | 256 |
+| [vit_medium_patch16_rope_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_medium_patch16_rope_reg1_gap_256.sbb_in1k)  | 83.81 | 96.824 | 38.74 | 256 |
+| [vit_betwixt_patch16_reg4_gap_256.sbb_in1k](https://huggingface.co/timm/vit_betwixt_patch16_reg4_gap_256.sbb_in1k)  | 83.706 | 96.616 | 60.4 | 256 |
+| [vit_betwixt_patch16_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_betwixt_patch16_reg1_gap_256.sbb_in1k)  | 83.628 | 96.544 | 60.4 | 256 |
+| [vit_medium_patch16_reg4_gap_256.sbb_in1k](https://huggingface.co/timm/vit_medium_patch16_reg4_gap_256.sbb_in1k)  | 83.47 | 96.622 | 38.88 | 256 |
+| [vit_medium_patch16_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_medium_patch16_reg1_gap_256.sbb_in1k)  | 83.462 | 96.548 | 38.88 | 256 |
+| [vit_little_patch16_reg4_gap_256.sbb_in1k](https://huggingface.co/timm/vit_little_patch16_reg4_gap_256.sbb_in1k)  | 82.514 | 96.262 | 22.52 | 256 |
+| [vit_pwee_patch16_reg1_gap_256.sbb_in1k](https://huggingface.co/timm/vit_pwee_patch16_reg1_gap_256.sbb_in1k)  | 80.072 | 95.136 | 15.25 | 256 |
+| [vit_mediumd_patch16_reg4_gap_256.sbb_in12k](https://huggingface.co/timm/vit_mediumd_patch16_reg4_gap_256.sbb_in12k) | N/A | N/A | 64.11 | 256 |
+| [vit_betwixt_patch16_reg4_gap_256.sbb_in12k](https://huggingface.co/timm/vit_betwixt_patch16_reg4_gap_256.sbb_in12k)  | N/A | N/A | 60.4 | 256 |
+
+* AttentionExtract helper added to extract attention maps from `timm` models. See example in https://github.com/huggingface/pytorch-image-models/discussions/1232#discussioncomment-9320949
+* `forward_intermediates()` API refined and added to more models including some ConvNets that have other extraction methods.
+* 1017 of 1047 model architectures support `features_only=True` feature extraction. Remaining 34 architectures can be supported but based on priority requests.
+* Remove torch.jit.script annotated functions including old JIT activations. Conflict with dynamo and dynamo does a much better job when used.
+
 ### April 11, 2024
 * Prepping for a long overdue 1.0 release, things have been stable for a while now.
 * Significant feature that's been missing for a while, `features_only=True` support for ViT models with flat hidden states or non-std module layouts (so far covering  `'vit_*', 'twins_*', 'deit*', 'beit*', 'mvitv2*', 'eva*', 'samvit_*', 'flexivit*'`)