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:
- 67502e8ea142b3b854ef321fd25914c968ef9d507b955bef4611715385c2ca61
- Size of remote file:
- 687 MB
- SHA256:
- 1fdbf49d7bfd2df4c5398d66c82285e8c56465af89eea03dc4359a18ac7c3612
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