Instructions to use google/maxim-s2-deraining-raindrop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use google/maxim-s2-deraining-raindrop with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://google/maxim-s2-deraining-raindrop") - Notebooks
- Google Colab
- Kaggle
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Model description
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This is the MAXIM model as described in [MAXIM: Multi-Axis MLP for Image Processing](https://arxiv.org/2201.02973) by Tu et al. The model was obtained by porting the official JAX params available [here](https://github.com/google-research/maxim). Porting code is available [here](https://github.com/sayakpaul/maxim-tf).
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## Intended uses & limitations
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The model was pre-trained on the RainDrop dataset and is intended to use for image deraining.
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