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
| { | |
| "do_affine_transform": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_processor_type": "VitPoseImageProcessor", | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "normalize_factor": 200.0, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 256, | |
| "width": 192 | |
| } | |
| } | |