Instructions to use jvdzwaan/ocrpostcorrection-task-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jvdzwaan/ocrpostcorrection-task-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jvdzwaan/ocrpostcorrection-task-1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jvdzwaan/ocrpostcorrection-task-1") model = AutoModelForTokenClassification.from_pretrained("jvdzwaan/ocrpostcorrection-task-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f1a2a211cdb82a1b32e704068a3bdad8f24bd6ed291257a962df5b304c49835
- Size of remote file:
- 709 MB
- SHA256:
- f934e23694921018a3562c552464ff223f64b52bcf37e7544c609df57724705b
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