Instructions to use goatrider/ocr-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use goatrider/ocr-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="goatrider/ocr-model")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("goatrider/ocr-model") model = AutoModelForTokenClassification.from_pretrained("goatrider/ocr-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 990d86b29cd9869277d25f5a314db19c31c860f26d9bf46e4ce09109cac8723f
- Size of remote file:
- 1.01 GB
- SHA256:
- 0522ea7521893d69bc92a44eb4d020b3a2e5d21a6da10e149cbf00ff6373c7a4
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