Instructions to use MBZUAI/swiftformer-l3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MBZUAI/swiftformer-l3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MBZUAI/swiftformer-l3") 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-l3") model = AutoModelForImageClassification.from_pretrained("MBZUAI/swiftformer-l3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 175 Bytes
0b87cc8 | 1 2 3 4 5 6 7 8 9 10 11 | {
"do_normalize": true,
"do_resize": true,
"image_mean": [
0.485, 0.456, 0.406
],
"image_std": [
0.229, 0.224, 0.225
],
"size": 224
} |