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Update README.md with new model card content
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README.md
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@@ -44,7 +44,7 @@ The following model checkpoints are provided by the Keras team. Weights have bee
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### Example Usage
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```python
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# Pretrained ResNet backbone.
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model = keras_hub.models.ResNetBackbone.from_preset("
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input_data = np.random.uniform(0, 1, size=(2, 224, 224, 3))
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model(input_data)
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)
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model(input_data)
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# Use resnet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("
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# User timm presets directly from hugingface
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/resnet101.a1_in1k')
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```python
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# Pretrained ResNet backbone.
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-
model = keras_hub.models.ResNetBackbone.from_preset("
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input_data = np.random.uniform(0, 1, size=(2, 224, 224, 3))
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model(input_data)
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)
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model(input_data)
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# Use resnet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("
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# User timm presets directly from hugingface
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/resnet101.a1_in1k')
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### Example Usage
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```python
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# Pretrained ResNet backbone.
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model = keras_hub.models.ResNetBackbone.from_preset("resnet_18_imagenet")
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input_data = np.random.uniform(0, 1, size=(2, 224, 224, 3))
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model(input_data)
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)
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model(input_data)
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# Use resnet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("resnet_18_imagenet")
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# User timm presets directly from hugingface
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/resnet101.a1_in1k')
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```python
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# Pretrained ResNet backbone.
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model = keras_hub.models.ResNetBackbone.from_preset("hf://keras/resnet_18_imagenet")
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input_data = np.random.uniform(0, 1, size=(2, 224, 224, 3))
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model(input_data)
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)
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model(input_data)
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# Use resnet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("hf://keras/resnet_18_imagenet")
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# User timm presets directly from hugingface
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/resnet101.a1_in1k')
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