Instructions to use hf-internal-testing/tiny-random-VitPoseForPoseEstimation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-VitPoseForPoseEstimation with Transformers:
# Load model directly from transformers import AutoImageProcessor, VitPoseForPoseEstimation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-VitPoseForPoseEstimation") model = VitPoseForPoseEstimation.from_pretrained("hf-internal-testing/tiny-random-VitPoseForPoseEstimation") - Notebooks
- Google Colab
- Kaggle
Upload model.onnx
Browse files- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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size 5056718
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