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:
- 3b300252c08b26c048ff2d3caf0e4a8b56e305b4a46da4a76fc48180c9f9ceb6
- Size of remote file:
- 5.11 kB
- SHA256:
- 8bf29a13745448625a3b394ca80643440981e1598a54e2d110d0449d5d8c4fa2
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