| ## Overview | |
| This model is a finetuned version of [mt5-small](https://huggingface.co/google/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](https://github.com/monatis/tqp) for any comments, suggestions or interesting findings when using this model. | |
| ## Usage | |
| You can generate 5 paraphrases for the input question with The simple code below. | |
| ```python | |
| 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: | |
| ```shell | |
| ['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?'] | |
| ``` | |
| ## Dataset | |
| I used [TQP dataset V0.1](https://github.com/monatis/tqp) 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. | |
| ## Citation | |
| If you find the dataset or model useful for your research, [consider citation](https://zenodo.org/record/4719801#.YIbI45AzZPZ). |