Instructions to use Mitsua/swin-base-multi-fractal-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mitsua/swin-base-multi-fractal-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mitsua/swin-base-multi-fractal-1k") 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("Mitsua/swin-base-multi-fractal-1k") model = AutoModelForImageClassification.from_pretrained("Mitsua/swin-base-multi-fractal-1k") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "ViTFeatureExtractor", | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 3, | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| } | |
| } | |