Create README.md

README.md

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+---
+license: mit
+language:
+- en
+tags:
+- spellchecking
+- NLP
+- T5
+- pytorch
+- natural language generation
+---
+
+# Card for T5-large-spell model
+
+### Summary
+The model corrects spelling errors and typos by bringing all words in the text to the standard English language.
+The proofreader was trained based on the [T5-large](https://huggingface.co/t5-large) model. 
+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).
+
+### Articles and speeches
+- [Speech about the SAGE library](https://youtu.be/yFfkV0Qjuu0), DataFest 2023
+- [Article about synthetic error generation methods](https://www.dialog-21.ru/media/5914/martynovnplusetal056.pdf), Dialogue 2023
+- [Article about SAGE and our best solution](https://arxiv.org/abs/2308.09435), Review EACL 2024
+
+### Examples
+| Input | Output |
+| --- | --- |
+| Th festeivаl was excelzecnt in many ways, and in particular it beinganinternational festjival sss a chаllenging, bet brilli an t ea. | The festival was excellent in many ways, and in particular it beinganinternational festival is a challenging, but brilliant one to see. |
+| That 's why I believe in the solution which is the closest to human nature and can help us to avoid boredome. I am sure that eventually we will take off our clothes and in the future we will be undressed and free. There wo n't be any problem with being up - do - date . | That's why I believe in the solution which is the closest to human nature and can help us to avoid boredom. I am sure that eventually we will take off our clothes and in the future we will be undressed and free. There won't be any problem with being up - do - date. |
+| If you bought something goregous, you well be very happy. | If you bought something gorgeous, you will be very happy. |
+
+## Metrics
+### Quality
+Below are automatic metrics for determining the correctness of the spell checkers. 
+We present a comparison of our solution both with open automatic spell checkers and with the ChatGPT family of models on two available datasets:
+- **BEA60K**: English spelling errors collected from several domains;
+- **JFLEG**: 1601 sentences in English, which contain about 2 thousand spelling errors;
+
+**BEA60K**
+| Model | Precision | Recall | F1 |
+| --- | --- | --- | --- |
+| T5-large-spell | 66.5 | 83.1 | 73.9 |
+| ChatGPT gpt-3.5-turbo-0301 | 66.9 | 84.1 | 74.5 |
+| ChatGPT gpt-4-0314 | 68.6 | 85.2 | 76.0 |
+| ChatGPT text-davinci-003 | 67.8 | 83.9 | 75.0 |
+| Bert (https://github.com/neuspell/neuspell) | 65.8 | 79.6 | 72.0 |
+| SC-LSTM (https://github.com/neuspell/neuspell) | 62.2 | 80.3 | 72.0 |
+
+**JFLEG**
+| Model | Precision | Recall | F1 |
+| --- | --- | --- | --- |
+| T5-large-spell | 83.4 | 84.3 | 83.8 |
+| ChatGPT gpt-3.5-turbo-0301 | 77.8 | 88.6 | 82.9 |
+| ChatGPT gpt-4-0314 | 77.9 | 88.3 | 82.8 |
+| ChatGPT text-davinci-003 | 76.8 | 88.5 | 82.2 |
+| Bert (https://github.com/neuspell/neuspell) | 78.5 | 85.4 | 81.8 |
+| SC-LSTM (https://github.com/neuspell/neuspell) | 80.6 | 86.1 | 83.2 |
+
+## How to use
+```python
+from transformers import T5ForConditionalGeneration, AutoTokenizer
+
+path_to_model = "<path_to_model>"
+
+model = T5ForConditionalGeneration.from_pretrained(path_to_model)
+tokenizer = AutoTokenizer.from_pretrained(path_to_model)
+prefix = "grammar: "
+
+sentence = "If you bought something goregous, you well be very happy."
+sentence = prefix + grammar
+
+encodings = tokenizer(sentence, return_tensors="pt")
+generated_tokens = model.generate(**encodings)
+answer = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+print(answer)
+
+# ["If you bought something gorgeous, you will be very happy."]
+```
+
+## Resources
+- [SAGE library code with augmentation methods, access to datasets and open models](https://github.com/orgs/ai-forever/sage), GitHub
+- [ruM2M100-1.2B](https://huggingface.co/ai-forever/RuM2M100-1.2B), HuggingFace
+- [ruM2M100-418M](https://huggingface.co/ai-forever/RuM2M100-420M), HuggingFace
+- [FredT5-large-spell](https://huggingface.co/ai-forever/FRED-T5-large-spell), HuggingFace
+- [T5-large-spell](https://huggingface.co/ai-forever/T5-large-spell), HuggingFace
+
+## License
+The [T5-large](https://huggingface.co/t5-large) model, on which our solution is based, and its source code are supplied under the APACHE-2.0 license. 
+Our solution is supplied under the MIT license.
+
+## Contacts
+For questions related to the operation and application of the model, please contact the product manager: Pavel Lebedev [email protected].