Instructions to use bswift/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bswift/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bswift/test") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, VisionTransformerForImageClassification processor = AutoImageProcessor.from_pretrained("bswift/test") model = VisionTransformerForImageClassification.from_pretrained("bswift/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92d355fb0c1fb5cad152710c1dd950771b08ea920d48fa9d2daf8f0660c677a2
- Size of remote file:
- 1.22 GB
- SHA256:
- 8858bda82f0d471403c350109077d68c28335ea3c63569f07ba68ec328411aa8
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