Instructions to use emergentai/cancer-efficientnetb7-undersampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use emergentai/cancer-efficientnetb7-undersampling with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://emergentai/cancer-efficientnetb7-undersampling") - Notebooks
- Google Colab
- Kaggle
Download cancer_efficientnetB7_undersampling.keras from emergentai/cancer-efficientnetb7-undersampling: direct link, hf CLI and curl.
- Browser
- Download file 321 MB
-
https://huggingface.co/emergentai/cancer-efficientnetb7-undersampling/resolve/c2b283c4f377aed65879fcabdaf168f8bbe04f91/cancer_efficientnetB7_undersampling.keras
- Command line
-
hf download hf://emergentai/cancer-efficientnetb7-undersampling@c2b283c4f377aed65879fcabdaf168f8bbe04f91/cancer_efficientnetB7_undersampling.keras
-
curl -L -o cancer_efficientnetB7_undersampling.keras https://huggingface.co/emergentai/cancer-efficientnetb7-undersampling/resolve/c2b283c4f377aed65879fcabdaf168f8bbe04f91/cancer_efficientnetB7_undersampling.keras
321 MB
- Xet hash:
- 5761071233cb49b5652a8980b2689cd535b9d75e7faeb6d6f0ace2fa396f7f53
- Size of remote file:
- 321 MB
- SHA256:
- 7b9cdcb809cd04c39a84c1c982d4ee8200cb600bf72605ab7c900ac177e38d03
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