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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e97d2afc0c8796f04ab9a7491267df0430ed69efdddcb12dd3a08d250d077e09
- Size of remote file:
- 687 MB
- SHA256:
- daac4e784c2a33ed1e165bbeb27347dcd9d60a621b6bdc02b1a6aa540d9a0ae5
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