Instructions to use softcatala/fullstop-catalan-punctuation-prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use softcatala/fullstop-catalan-punctuation-prediction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="softcatala/fullstop-catalan-punctuation-prediction")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("softcatala/fullstop-catalan-punctuation-prediction") model = AutoModelForTokenClassification.from_pretrained("softcatala/fullstop-catalan-punctuation-prediction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Better documentation
Browse files
README.md
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@@ -24,12 +24,12 @@ The performance differs for the single punctuation markers as hyphens and colons
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| Label | CA |
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| ------------- | ----- |
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| macro average | 0.84 |
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## Contact
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| Label | CA |
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| ------------- | ----- |
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| macro average | 0.84 |
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## Contact
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model.txt
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id: 13
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date: 2022-4-03
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tokenization: split
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