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
Update README.md
Browse files- fix language cz -> cs
- remove sentence about metrics
README.md
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language:
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## Results
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Loss and F1 measure on separate languages.
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| Set | Loss |
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| -- | -- |
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| Train | 0.224500 |
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language:
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- bg
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- cs
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- de
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- en
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- es
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## Results
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| Set | Loss |
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| -- | -- |
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| Train | 0.224500 |
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