Instructions to use MBZUAI/swiftformer-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBZUAI/swiftformer-s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MBZUAI/swiftformer-s") 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("MBZUAI/swiftformer-s") model = AutoModelForImageClassification.from_pretrained("MBZUAI/swiftformer-s") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.485, 0.456, 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, 0.224, 0.225 | |
| ], | |
| "size": 224 | |
| } |