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efficientnet_b0_ra_imagenet

Image Classification
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  1. README.md +32 -0
  2. config.json +98 -0
  3. image_converter.json +33 -0
  4. metadata.json +6 -0
  5. model.weights.h5 +3 -0
  6. preprocessor.json +51 -0
  7. task.json +161 -0
  8. task.weights.h5 +3 -0
README.md ADDED
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+ ---
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+ library_name: keras-hub
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+ ---
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+ This is a [`EfficientNet` model](https://keras.io/api/keras_hub/models/efficient_net) uploaded using the KerasHub library and can be used with JAX, TensorFlow, and PyTorch backends.
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+ This model is related to a `ImageClassifier` task.
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+
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+ Model config:
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+ * **name:** efficient_net_backbone
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+ * **trainable:** True
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+ * **width_coefficient:** 1.0
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+ * **depth_coefficient:** 1.0
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+ * **dropout:** 0
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+ * **depth_divisor:** 8
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+ * **min_depth:** None
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+ * **activation:** swish
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+ * **input_shape:** [None, None, 3]
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+ * **stackwise_kernel_sizes:** [3, 3, 5, 3, 5, 5, 3]
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+ * **stackwise_num_repeats:** [1, 2, 2, 3, 3, 4, 1]
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+ * **stackwise_input_filters:** [32, 16, 24, 40, 80, 112, 192]
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+ * **stackwise_expansion_ratios:** [1, 6, 6, 6, 6, 6, 6]
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+ * **stackwise_squeeze_and_excite_ratios:** [0.25, 0.25, 0.25, 0.25, 0.25, 0.25, 0.25]
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+ * **stackwise_strides:** [1, 2, 2, 2, 1, 2, 1]
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+ * **stackwise_block_types:** ['v1', 'v1', 'v1', 'v1', 'v1', 'v1', 'v1']
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+ * **include_stem_padding:** True
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+ * **use_depth_divisor_as_min_depth:** True
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+ * **cap_round_filter_decrease:** True
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+ * **stem_conv_padding:** valid
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+ * **batch_norm_momentum:** 0.9
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+ * **batch_norm_epsilon:** 1e-05
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+
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+ This model card has been generated automatically and should be completed by the model author. See [Model Cards documentation](https://huggingface.co/docs/hub/model-cards) for more information.
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