Instructions to use zeromodels/tf_efficientnet_lite0_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/tf_efficientnet_lite0_in1k with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/tf_efficientnet_lite0_in1k") - Keras
How to use zeromodels/tf_efficientnet_lite0_in1k with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/tf_efficientnet_lite0_in1k") - Notebooks
- Google Colab
- Kaggle
Fix Collection badge link to the current zeromodels collection slug
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README.md
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## ***See [our collection](https://huggingface.co/collections/zeromodels/efficientnet-lite-
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# Run EfficientNet-Lite with Keras 3: JAX, PyTorch, or TensorFlow
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[](https://github.com/IMvision12/ZeroModels) [](https://imvision12.github.io/ZeroModels/classification_backbones/) [](https://huggingface.co/collections/zeromodels/efficientnet-lite-
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# zeromodels/tf_efficientnet_lite0_in1k
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## ***See [our collection](https://huggingface.co/collections/zeromodels/efficientnet-lite-6a8eae80388ae9631ea12c91) for all versions of EfficientNet-Lite.***
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# Run EfficientNet-Lite with Keras 3: JAX, PyTorch, or TensorFlow
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[](https://github.com/IMvision12/ZeroModels) [](https://imvision12.github.io/ZeroModels/classification_backbones/) [](https://huggingface.co/collections/zeromodels/efficientnet-lite-6a8eae80388ae9631ea12c91)
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# zeromodels/tf_efficientnet_lite0_in1k
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