Instructions to use data-silence/predict-plates with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use data-silence/predict-plates with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="data-silence/predict-plates") 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("data-silence/predict-plates") model = AutoModelForImageClassification.from_pretrained("data-silence/predict-plates", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 399339be9348db0147d2775b0c2dbd4aa22d7345870598810155e994d52dd100
- Size of remote file:
- 343 MB
- SHA256:
- 874ab8fa88597b981d3ad87af338fed7d72084dde31bb352d580142fccfdb089
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