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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed4a1e929497d952c4c006aac683c2fa063a8e31b57e87b1e23b7959900f2faa
- Size of remote file:
- 372 MB
- SHA256:
- a48511f8041ed23d8ef6b866fe8caa56e19c19323d43b36de4b39b7da0a53f3d
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