Instructions to use hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-to-image", model="hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageToImage processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution") model = AutoModelForImageToImage.from_pretrained("hf-internal-testing/tiny-random-Swin2SRForImageSuperResolution", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
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Update tiny models for Swin2SRForImageSuperResolution
#1 opened almost 3 years ago
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