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Parent(s):
04cac80
Update README.md with new model card content
Browse files
README.md
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@@ -39,7 +39,7 @@ The following model checkpoints are provided by the Keras team. Weights have bee
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input_data = np.ones(shape=(8, 224, 224, 3))
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# Pretrained backbone
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model = keras_hub.models.DenseNetBackbone.from_preset("
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model(input_data)
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# Randomly initialized backbone with a custom config
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@@ -49,7 +49,7 @@ model = keras_hub.models.DenseNetBackbone(
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model(input_data)
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# Use densenet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("
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# User Timm presets directly from HuggingFace
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/densenet121.tv_in1k')
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@@ -61,7 +61,7 @@ model = keras_hub.models.ImageClassifier.from_preset('hf://timm/densenet121.tv_i
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input_data = np.ones(shape=(8, 224, 224, 3))
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# Pretrained backbone
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model = keras_hub.models.DenseNetBackbone.from_preset("
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model(input_data)
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# Randomly initialized backbone with a custom config
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@@ -71,7 +71,7 @@ model = keras_hub.models.DenseNetBackbone(
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model(input_data)
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# Use densenet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("
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# User Timm presets directly from HuggingFace
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/densenet121.tv_in1k')
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input_data = np.ones(shape=(8, 224, 224, 3))
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# Pretrained backbone
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model = keras_hub.models.DenseNetBackbone.from_preset("densenet_201_imagenet")
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model(input_data)
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# Randomly initialized backbone with a custom config
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model(input_data)
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# Use densenet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("densenet_201_imagenet")
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# User Timm presets directly from HuggingFace
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/densenet121.tv_in1k')
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input_data = np.ones(shape=(8, 224, 224, 3))
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# Pretrained backbone
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model = keras_hub.models.DenseNetBackbone.from_preset("hf://keras/densenet_201_imagenet")
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model(input_data)
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# Randomly initialized backbone with a custom config
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model(input_data)
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# Use densenet for image classification task
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model = keras_hub.models.ImageClassifier.from_preset("hf://keras/densenet_201_imagenet")
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# User Timm presets directly from HuggingFace
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model = keras_hub.models.ImageClassifier.from_preset('hf://timm/densenet121.tv_in1k')
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