Instructions to use ivensamdh/swinv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivensamdh/swinv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ivensamdh/swinv2") 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("ivensamdh/swinv2") model = AutoModelForImageClassification.from_pretrained("ivensamdh/swinv2") - Notebooks
- Google Colab
- Kaggle
Adding ONNX file of this model
#1
by ivensamdh - opened
- model.onnx +3 -0
model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:f349a8d310e65f93f9d8ddde06a261bf202237b4f23588c0ae2075a0e58b0651
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size 365254664
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