Instructions to use facebook/levit-128S with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/levit-128S with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/levit-128S") 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("facebook/levit-128S") model = AutoModelForImageClassification.from_pretrained("facebook/levit-128S") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9b94b8944bc22cefee094e770ef8387f2ed4f16bc3272dca3eb8f81e62c51f1
- Size of remote file:
- 32.1 MB
- SHA256:
- 0e2d4e377c1b6e0df2f2e7132e240a71aadc761a61360c8060019829af83d33a
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