Instructions to use MITCriticalData/Sentinel-2_Resnet50V2_Autoencoder_RGB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use MITCriticalData/Sentinel-2_Resnet50V2_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_Resnet50V2_Autoencoder_RGB") - Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
b3afe33 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1 oid sha256:2175da3ac1066a236cdd9f23c137205be89282cd81fb2e608558cb69667be6f9 size 5444346 |