Instructions to use prithivMLmods/Painting-126-DomainNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Painting-126-DomainNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Painting-126-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/Painting-126-DomainNet") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Painting-126-DomainNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98522bfc7af2c3ea4ca649fd9f46a9ddff912a2ddda82975f1de4843a17f84ce
- Size of remote file:
- 5.3 kB
- SHA256:
- 454d8d6d2afd6896b7d11d289c6f756bd8a79d383926589457d422cd30c563a6
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