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This model is a finetuned version of mt5-small for question paraphrasing task in Turkish. As a generator model, its capabilities are currently investigated and there is an ongoing effort to further improve it. You can raise an issue in this GitHub repo for any comments, suggestions or interesting findings when using this model.


You can generate 5 paraphrases for the input question with The simple code below.

from transformers import AutoTokenizer, T5ForConditionalGeneration
model_name = "mys/mt5-small-turkish-question-paraphrasing"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)

tokens = tokenizer.encode_plus("Yarın toplantı kaçta başlıyor?", return_tensors='pt')
paraphrases = model.generate(tokens['input_ids'], max_length=128, num_return_sequences=5, num_beams=5)
tokenizer.batch_decode(paraphrases, skip_special_tokens=True)

And the output will be something like:

['Yarın toplantı ne zaman başlıyor?',
 'Yarın toplantı saat kaçta başlıyor?',
 'Yarın toplantı saat kaçta başlar?',
 'Yarın toplantı ne zaman başlayacak?',
 'Yarın toplantı ne zaman başlar?']


I used TQP dataset V0.1 that I've published just recently. This model should be taken as as a baseline model for TQP dataset. A cleaning and further improvements in the dataset and an elaborate hyperparameter tuning may boost the performance.


If you find the dataset or model useful for your research, consider citation.

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