Instructions to use darklorddad/Model-SwinV2-Tiny-83 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darklorddad/Model-SwinV2-Tiny-83 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="darklorddad/Model-SwinV2-Tiny-83") 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("darklorddad/Model-SwinV2-Tiny-83") model = AutoModelForImageClassification.from_pretrained("darklorddad/Model-SwinV2-Tiny-83") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfca554996159850c75926eb6761920e502807af913b819a1722ac14b482f636
- Size of remote file:
- 5.3 kB
- SHA256:
- 1da0df3ee160ed78a94d79268add1dd382f9eb019c94de90bf1adfdeaace04bb
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