Instructions to use isp-uv-es/superIX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use isp-uv-es/superIX with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("isp-uv-es/superIX") - Notebooks
- Google Colab
- Kaggle
Update ldm_baseline/run.py
Browse files- ldm_baseline/run.py +2 -2
ldm_baseline/run.py
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@@ -36,6 +36,6 @@ ax[2].set_title("HR")
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plt.show()
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# Run the experiment
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# benchmark.create_geotiff(model, run_diffuser,
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# benchmark.run(["naip"])
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# benchmark.plot(["naip"])
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plt.show()
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# Run the experiment
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# benchmark.create_geotiff(model, run_diffuser, "all", "ldm_baseline/")
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# benchmark.run(["naip"])
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# benchmark.plot(["naip"])
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