Instructions to use MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB 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://MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB") - Notebooks
- Google Colab
- Kaggle
Download variables/variables.data-00000-of-00001 from MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB: direct link, hf CLI and curl.
- Browser
- Download file 349 MB
-
https://huggingface.co/MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB/resolve/main/variables/variables.data-00000-of-00001
- Command line
-
hf download hf://MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB/variables/variables.data-00000-of-00001
-
curl -L -o variables.data-00000-of-00001 https://huggingface.co/MITCriticalData/Sentinel-2_ViT_Autoencoder_RGB/resolve/main/variables/variables.data-00000-of-00001
349 MB
- Xet hash:
- 0876fc85566cfc906c9f7d028ec04e30e82c64770654bbc58d921f8c1010e1ec
- Size of remote file:
- 349 MB
- SHA256:
- 2e3a52183bf2926576a1230d28d1cab5fcc7b49a34ceb36a31f82bc5bab0478b
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