Instructions to use gagan3012/swinv2_1024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gagan3012/swinv2_1024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gagan3012/swinv2_1024") 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("gagan3012/swinv2_1024") model = AutoModelForImageClassification.from_pretrained("gagan3012/swinv2_1024") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd467d296b87db287576323a430c3f4ee19c4df6d5a06e80445cd3a1f9cd346f
- Size of remote file:
- 113 MB
- SHA256:
- 0ea1df89f964bcdf6fd1e988a155e004e4fa3bd01a4d92dae757fdb48db76781
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