Instructions to use prithivMLmods/Multisource-121-DomainNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Multisource-121-DomainNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Multisource-121-DomainNet") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Multisource-121-DomainNet") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Multisource-121-DomainNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b10f37402a2978891f111e0c61c5e13a84bff1acd66c56360b6c870f9ab5dca
- Size of remote file:
- 687 MB
- SHA256:
- d9cfa7be0915bddb120a1676cbf1b331993bcb3f9404f2e428f1099b7d570f8e
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