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Fix 3 typos in README.md
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README.md

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@@ -137,7 +137,7 @@
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* Allow override of `cache_dir` arg for model creation
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* Pass through `trust_remote_code` for HF datasets wrapper
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* `inception_next_atto` model added by creator
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* Adan optimizer caution, and Lamb decoupled weighgt decay options
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* Adan optimizer caution, and Lamb decoupled weight decay options
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* Some feature_info metadata fixed by https://github.com/brianhou0208
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* All OpenCLIP and JAX (CLIP, SigLIP, Pali, etc) model weights that used load time remapping were given their own HF Hub instances so that they work with `hf-hub:` based loading, and thus will work with new Transformers `TimmWrapperModel`
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@@ -301,7 +301,7 @@ Add a set of new very well trained ResNet & ResNet-V2 18/34 (basic block) weight
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* Other misc fixes
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### June 24, 2024
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* 3 more MobileNetV4 hyrid weights with different MQA weight init scheme
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* 3 more MobileNetV4 hybrid weights with different MQA weight init scheme
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| model |top1 |top1_err|top5 |top5_err|param_count|img_size|
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|--------------------------------------------------------------------------------------------------|------|--------|------|--------|-----------|--------|
@@ -344,7 +344,7 @@ Add a set of new very well trained ResNet & ResNet-V2 18/34 (basic block) weight
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### May 14, 2024
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* Support loading PaliGemma jax weights into SigLIP ViT models with average pooling.
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* Add Hiera models from Meta (https://github.com/facebookresearch/hiera).
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* Add `normalize=` flag for transforms, return non-normalized torch.Tensor with original dytpe (for `chug`)
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* Add `normalize=` flag for transforms, return non-normalized torch.Tensor with original dtype (for `chug`)
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* Version 1.0.3 release
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### May 11, 2024

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