Instructions to use apple/mobilevitv2-1.0-imagenet1k-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apple/mobilevitv2-1.0-imagenet1k-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="apple/mobilevitv2-1.0-imagenet1k-256") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, MobileViTv2ForImageClassification processor = AutoImageProcessor.from_pretrained("apple/mobilevitv2-1.0-imagenet1k-256") model = MobileViTv2ForImageClassification.from_pretrained("apple/mobilevitv2-1.0-imagenet1k-256", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
6229cf2 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:895b830a71a8cce260b2f45d2691d1bd075e843b9d5182f778b5c07d23ae2933
size 19764225
|