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Den4ikAI/ruT5-small-interpreter

Модель для восстановления фразы с помощью контекста диалога (анафора, эллипсисы, гэппинг), проверки орфографии и нормализации текста диалоговых реплик.

Больше о задаче тут.

Пример использования

import torch
from transformers import T5ForConditionalGeneration, T5Tokenizer
model_name = 'Den4ikAI/ruT5-small-interpreter'
tokenizer = T5Tokenizer.from_pretrained(model_name)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = T5ForConditionalGeneration.from_pretrained(model_name)
model.eval()
t5_input = '''- Ты собак любишь?
- Не люблю я их  #'''
input_ids = tokenizer(t5_input, return_tensors='pt').input_ids
out_ids = model.generate(input_ids=input_ids, max_length=100, eos_token_id=tokenizer.eos_token_id, early_stopping=True)
t5_output = tokenizer.decode(out_ids[0][1:])
print(t5_output)

Citation

@MISC{Den4ikAI/ruT5-small-interpreter,
    author  = {Denis Petrov, Ilya Koziev},
    title   = {Russian conversations interpreter and normalizer},
    url     = {https://huggingface.co/Den4ikAI/ruT5-small-interpreter},
    year    = 2023
}
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64.6M params
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F32
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Dataset used to train Den4ikAI/ruT5-small-interpreter