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