Instructions to use ritwik098/Licplatesdetection-train-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ritwik098/Licplatesdetection-train-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ritwik098/Licplatesdetection-train-finetuned")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ritwik098/Licplatesdetection-train-finetuned") model = AutoModelForObjectDetection.from_pretrained("ritwik098/Licplatesdetection-train-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a155878a381de89d9f12f7544d85f53bfb2a3bff516e551035d7c57526818652
- Size of remote file:
- 5.37 kB
- SHA256:
- 760f3761c56f91903c9208cbeef00bac687603cde20f927676e2f3a99bda216b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.