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")# pip install -U transformers accelerate # 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
Download checkpoint-4084/optimizer.pt from prithivMLmods/Multisource-121-DomainNet: direct link, hf CLI and curl.
- Browser
- Download file 687 MB
-
https://huggingface.co/prithivMLmods/Multisource-121-DomainNet/resolve/main/checkpoint-4084/optimizer.pt
- Command line
-
hf download hf://prithivMLmods/Multisource-121-DomainNet/checkpoint-4084/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/prithivMLmods/Multisource-121-DomainNet/resolve/main/checkpoint-4084/optimizer.pt
687 MB
- Xet hash:
- 8fef6d1d959fcbb141064cb3d3803081abc01f1d34a0674e146d9ea0c32ee4e6
- Size of remote file:
- 687 MB
- SHA256:
- 21cadc3833dfffbc9d4ef27ab50c1322e366e8b755e1ebf54fa2a89793353376
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