Instructions to use stevenbucaille/disk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stevenbucaille/disk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="stevenbucaille/disk", trust_remote_code=True)# Load model directly from transformers import AutoModelForKeypointDetection model = AutoModelForKeypointDetection.from_pretrained("stevenbucaille/disk", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_grayscale": false, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_processor_type": "LightGlueImageProcessor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 480, | |
| "width": 640 | |
| } | |
| } | |