Instructions to use mervess/FCD-Solar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use mervess/FCD-Solar 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://mervess/FCD-Solar") - Notebooks
- Google Colab
- Kaggle
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README.md
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For the inputs, Fourier components, it is for normalization.
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For the outputs, reconstructed solar flare images, it is to have a steady flux intensity range.
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#### Training Hyperparameters
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- **Hours used:** 2.5 hours
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- **Training Type:** Standard training
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## Technical Specifications
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Overcomplete Autoencoder trained in a supervised manner to reconstruct solar flare images from the Fourier components.
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### Compute Infrastructure
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For the inputs, Fourier components, it is for normalization.
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For the outputs, reconstructed solar flare images, it is to have a steady flux intensity range.
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#### Training Hyperparameters
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- **Hours used:** 2.5 hours
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- **Training Type:** Standard training
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## Technical Specifications
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Overcomplete Autoencoder trained in a supervised manner to reconstruct solar flare images from the Fourier components.
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### Compute Infrastructure
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