Instructions to use RUPunct/RUPunct_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RUPunct/RUPunct_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="RUPunct/RUPunct_small")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("RUPunct/RUPunct_small") model = AutoModelForTokenClassification.from_pretrained("RUPunct/RUPunct_small") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -90,8 +90,6 @@ while 1:
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preds = classifier(input_text)
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output = ""
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for item in preds:
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if item["word"] == ".":
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item["entity_group"] = "O"
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output += " " + process_token(item['word'].strip(), item['entity_group'])
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print(">>>", output)
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```
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preds = classifier(input_text)
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output = ""
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for item in preds:
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output += " " + process_token(item['word'].strip(), item['entity_group'])
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print(">>>", output)
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```
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