Instructions to use Bhavi23/DenseNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Bhavi23/DenseNet with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Bhavi23/DenseNet") - Notebooks
- Google Colab
- Kaggle
Upload densenet_checkpoint.weights.h5
Browse files
densenet_checkpoint.weights.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:74821579706e4edb33ab527b960da29c21b7860aa503b153b7329ebd51d7581b
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size 173544584
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