Instructions to use MBZUAI/swiftformer-xs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBZUAI/swiftformer-xs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MBZUAI/swiftformer-xs") 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("MBZUAI/swiftformer-xs") model = AutoModelForImageClassification.from_pretrained("MBZUAI/swiftformer-xs") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db8b2491713d1d0ccb82f998073351f9b6adc64fac2b21ca059b8f8aabb948a2
- Size of remote file:
- 14 MB
- SHA256:
- 4d208bc17e403f959bfb487ec3af1f6fc18e97ac5fbf7cd1d577fe38c1273446
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