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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## Uses
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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## How to Get Started with the Model
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Only TF-Keras (v. 2.15.0) is sufficient to run the model.
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## Citation
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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**APA:**
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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## More Information [optional]
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## Model Card Contact
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## Uses
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The model takes 48 real numbers (of Fourier components, combined real and imaginary) as input, and reconstructs a 128x128 image corresponding to them.
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## How to Get Started with the Model
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Only TF-Keras (v. 2.15.0) is sufficient to run the model.
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## Citation
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Selcuk-Simsek, M., Massa, P., Xiao, H. et al. Fourier convolutional decoder: reconstructing solar flare images via deep learning. Neural Comput & Applic (2025). https://doi.org/10.1007/s00521-025-11283-6
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## Model Card Contact
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