Add tiny/small in12k pretrained and fine-tuned ConvNeXt models
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@ -24,6 +24,12 @@ And a big thanks to all GitHub sponsors who helped with some of my costs before
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* ❗Updates after Oct 10, 2022 are available in 0.8.x pre-releases (`pip install --pre timm`) or cloning main❗
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* Stable releases are 0.6.x and available by normal pip install or clone from [0.6.x](https://github.com/rwightman/pytorch-image-models/tree/0.6.x) branch.
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### Jan 11, 2023
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* Update ConvNeXt ImageNet-12k pretrain series w/ two new fine-tuned weights (and pre FT `.in12k` tags)
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* `convnext_nano.in12k_ft_in1k` - 82.3 @ 224, 82.9 @ 288 (previously released)
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* `convnext_tiny.in12k_ft_in1k` - 84.2 @ 224, 84.5 @ 288
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* `convnext_small.in12k_ft_in1k` - 85.2 @ 224, 85.3 @ 288
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### Jan 6, 2023
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* Finally got around to adding `--model-kwargs` and `--opt-kwargs` to scripts to pass through rare args directly to model classes from cmd line
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* `train.py /imagenet --model resnet50 --amp --model-kwargs output_stride=16 act_layer=silu`
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@ -478,10 +478,22 @@ default_cfgs = generate_default_cfgs({
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url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/convnext_tiny_hnf_a2h-ab7e9df2.pth',
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hf_hub_id='timm/',
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crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0),
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'convnext_tiny.in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0),
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'convnext_small.in12k_ft_in1k': _cfg(
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hf_hub_id='timm/',
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crop_pct=0.95, test_input_size=(3, 288, 288), test_crop_pct=1.0),
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'convnext_nano.in12k': _cfg(
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hf_hub_id='timm/',
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crop_pct=0.95, num_classes=11821),
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'convnext_tiny.in12k': _cfg(
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hf_hub_id='timm/',
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crop_pct=0.95, num_classes=11821),
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'convnext_small.in12k': _cfg(
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hf_hub_id='timm/',
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crop_pct=0.95, num_classes=11821),
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'convnext_tiny.fb_in1k': _cfg(
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url="https://dl.fbaipublicfiles.com/convnext/convnext_tiny_1k_224_ema.pth",
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