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Update README.md
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README.md
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@@ -21,7 +21,6 @@ An extensive dataset with “artificial” errors was taken as a training corpus
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- [SAGE library announcement](https://youtu.be/yFfkV0Qjuu0), DataFest 2023
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- [Paper about synthetic error generation methods](https://www.dialog-21.ru/media/5914/martynovnplusetal056.pdf), Dialogue 2023
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- [Paper about SAGE and our best solution](https://arxiv.org/abs/2308.09435), Review EACL 2024
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- Path to model = "ai-forever/FRED-T5-large-spell"
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### Examples
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*Examples are given with default generation parameters
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```python
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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path_to_model = "
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model = T5ForConditionalGeneration.from_pretrained(path_to_model)
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tokenizer = AutoTokenizer.from_pretrained(path_to_model, eos_token="</s>")
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- [SAGE library announcement](https://youtu.be/yFfkV0Qjuu0), DataFest 2023
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- [Paper about synthetic error generation methods](https://www.dialog-21.ru/media/5914/martynovnplusetal056.pdf), Dialogue 2023
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- [Paper about SAGE and our best solution](https://arxiv.org/abs/2308.09435), Review EACL 2024
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### Examples
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*Examples are given with default generation parameters
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```python
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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path_to_model = "ai-forever/FRED-T5-large-spell"
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model = T5ForConditionalGeneration.from_pretrained(path_to_model)
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tokenizer = AutoTokenizer.from_pretrained(path_to_model, eos_token="</s>")
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