Instructions to use swww/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use swww/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="swww/test") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("swww/test") model = AutoModelForImageClassification.from_pretrained("swww/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da633745ba109d0037081f06195944170eb0936a12cb9f56099ea46b23ae179f
- Size of remote file:
- 343 MB
- SHA256:
- 4e8bd57ab1e0cbbeb78fd33cde1c0d6d365ec17f7d1a0febd5191fb61ee829b1
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