Instructions to use keras/efficientnet_em_ra2_imagenet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/efficientnet_em_ra2_imagenet with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/efficientnet_em_ra2_imagenet") - Keras
How to use keras/efficientnet_em_ra2_imagenet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/efficientnet_em_ra2_imagenet") - Notebooks
- Google Colab
- Kaggle
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* [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946)(ICML 2019)
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* [Based on the original keras.applications EfficientNet](https://github.com/keras-team/keras/blob/master/keras/applications/efficientnet.py)
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* [EfficientNetV2: Smaller Models and Faster Training](https://arxiv.org/abs/2104.00298) (ICML 2021)
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* [EfficientNet API Documentation](
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* [KerasHub Beginner Guide](https://keras.io/guides/keras_hub/getting_started/)
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* [KerasHub Model Publishing Guide](https://keras.io/guides/keras_hub/upload/)
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* [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946)(ICML 2019)
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* [Based on the original keras.applications EfficientNet](https://github.com/keras-team/keras/blob/master/keras/applications/efficientnet.py)
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* [EfficientNetV2: Smaller Models and Faster Training](https://arxiv.org/abs/2104.00298) (ICML 2021)
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* [EfficientNet API Documentation](https://keras.io/keras_hub/api/models/efficientnet/)
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* [KerasHub Beginner Guide](https://keras.io/guides/keras_hub/getting_started/)
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* [KerasHub Model Publishing Guide](https://keras.io/guides/keras_hub/upload/)
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