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--- |
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license: mit |
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language: |
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- ru |
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metrics: |
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- seqeval |
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tags: |
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- generated-from-trainer |
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- restore_punctuation |
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widget: |
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- text: почему она ушла несмотря на то что ей было хорошо |
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- text: привет как дела |
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- text: сколько денег нужно чтобы стать счастливым |
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- text: это было сильно смело но глупо |
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--- |
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# ruBert-base for Punctuation Correction |
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The model is built upon the foundation of [ruBert-base](https://huggingface.co/ai-forever/ruBert-base) and has been fine-tuned to correctly place punctuation marks in Russian sentences (it predicts the mark after each word). |
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Some additional info about the model: |
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- **Fine-Tuning Source:** The model has undergone fine-tuning using a diverse dataset comprising over 20,000 paragraphs from Russian literary works. |
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- **Supported Classes:** The model is designed to predict classes following specific punctuation marks: ? ! . , : ... and space (as class O). |
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- **Input Format:** To achieve optimal results, input text should be provided without punctuation marks. The model does not process changes in letter case. |
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## Usage Guidelines |
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To use the model effectively, follow these guidelines: |
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1. **Input Text:** Feed the model with text excluding punctuation marks. |
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2. **Letter Case:** The model does not recognize changes in letter case. |
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## Authors |
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- Mark Stolyarov |
