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:
- 821a446021e5d6603ac7a264a74ba57cbaf94eb1d45ad942d221067cad9f20f4
- Size of remote file:
- 687 MB
- SHA256:
- 45359769ce363f07fdafc67a3880f22848e75a57d269b7e544eafe492a9f18b2
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