Instructions to use shauray/ViTPose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shauray/ViTPose with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, ViTPoseForPoseEstimation processor = AutoImageProcessor.from_pretrained("shauray/ViTPose") model = ViTPoseForPoseEstimation.from_pretrained("shauray/ViTPose", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from shauray/ViTPose: direct link, hf CLI and curl.
- Browser
- Download file 97.2 MB
-
https://huggingface.co/shauray/ViTPose/resolve/a4c7fec73a4e3cf239d263cbca15e46f0b25be35/pytorch_model.bin
- Command line
-
hf download hf://shauray/ViTPose@a4c7fec73a4e3cf239d263cbca15e46f0b25be35/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/shauray/ViTPose/resolve/a4c7fec73a4e3cf239d263cbca15e46f0b25be35/pytorch_model.bin
97.2 MB
- Xet hash:
- 5288dc5e1d3620d966141fed6d96a8e212ba93a4d9aba55830c756ef97d3db62
- Size of remote file:
- 97.2 MB
- SHA256:
- 44b641ef0604626eb9d898fd41cf01d76ea16206008ef542553bc77c4e259dd3
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