Instructions to use logasja/auramask-ensemble-crema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use logasja/auramask-ensemble-crema 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://logasja/auramask-ensemble-crema") - Notebooks
- Google Colab
- Kaggle
Download metadata.json from logasja/auramask-ensemble-crema: direct link, hf CLI and curl.
- Browser
- Download file 63 Bytes
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https://huggingface.co/logasja/auramask-ensemble-crema/resolve/main/metadata.json
- Command line
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hf download hf://logasja/auramask-ensemble-crema/metadata.json
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curl -L -o metadata.json https://huggingface.co/logasja/auramask-ensemble-crema/resolve/main/metadata.json
63 Bytes
| {"keras_version": "3.8.0", "date_saved": "2025-03-02@11:00:31"} |