Instructions to use MITCriticalData/Sentinel-2_ViT_Autoencoder_12Bands with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MITCriticalData/Sentinel-2_ViT_Autoencoder_12Bands with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://MITCriticalData/Sentinel-2_ViT_Autoencoder_12Bands") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd4d4eb37966ce3915df71de47d1b8936522c45cd519e96931e19c9dbd4f75e8
- Size of remote file:
- 761 MB
- SHA256:
- a42a355c2bcecdb515c9b9c41333ca91aaef2bd1d5a5d4c1e085b79d2d932919
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