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  ### Summary
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  The model corrects spelling errors and typos by bringing all words in the text to the standard English language.
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  The proofreader was trained based on the [T5-large](https://huggingface.co/t5-large) model.
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- An extensive dataset with “artificial” errors was taken as a training corpus: the corpus was assembled on the basis of the English-language Wikipedia and News blogs, then typos and spelling errors were automatically introduced into it using the functionality of the [SAGE library](https://github.com/orgs/ai-forever/sage).
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  ### Public references
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  - [SAGE library announcement](https://youtu.be/yFfkV0Qjuu0), DataFest 2023
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  ```
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  ## Resources
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- - [SAGE library](https://github.com/orgs/ai-forever/sage), GitHub
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  - [ruM2M100-1.2B](https://huggingface.co/ai-forever/RuM2M100-1.2B), HuggingFace
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  - [ruM2M100-418M](https://huggingface.co/ai-forever/RuM2M100-420M), HuggingFace
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  - [FredT5-large-spell](https://huggingface.co/ai-forever/FRED-T5-large-spell), HuggingFace
 
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  ### Summary
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  The model corrects spelling errors and typos by bringing all words in the text to the standard English language.
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  The proofreader was trained based on the [T5-large](https://huggingface.co/t5-large) model.
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+ An extensive dataset with “artificial” errors was taken as a training corpus: the corpus was assembled on the basis of the English-language Wikipedia and News blogs, then typos and spelling errors were automatically introduced into it using the functionality of the [SAGE library](https://github.com/ai-forever/sage).
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  ### Public references
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  - [SAGE library announcement](https://youtu.be/yFfkV0Qjuu0), DataFest 2023
 
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  ```
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  ## Resources
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+ - [SAGE library](https://github.com/ai-forever/sage), GitHub
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  - [ruM2M100-1.2B](https://huggingface.co/ai-forever/RuM2M100-1.2B), HuggingFace
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  - [ruM2M100-418M](https://huggingface.co/ai-forever/RuM2M100-420M), HuggingFace
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  - [FredT5-large-spell](https://huggingface.co/ai-forever/FRED-T5-large-spell), HuggingFace