First Readme

README.md

@@ -0,0 +1,45 @@
+---
+language: 
+- tr
+tags:
+- paraphrasing
+- encoder-decoder
+- seq2seq
+- bert
+---
+
+#Bert2Bert Turkish Paraphrase Generation
+
+#INISTA 2021
+
+#Comparison of Turkish Paraphrase Generation Models
+
+#Dataset
+
+The dataset used in model training was created with the combination of the translation of the QQP dataset and manually generated dataset.
+Dataset [Link](https://drive.google.com/file/d/1-2l9EwIzXZ7fUkNW1vdeF3lzQp2pygp_/view?usp=sharing) 
+
+#How To Use
+```python
+from transformers import BertTokenizerFast,EncoderDecoderModel
+tokenizer=BertTokenizerFast.from_pretrained("dbmdz/bert-base-turkish-cased")
+model = EncoderDecoderModel.from_pretrained("ahmetbagci/bert2bert-turkish-paraphrase-generation")
+
+text="son model arabalar çevreye daha mı az zarar veriyor?"
+input_ids = tokenizer(article, return_tensors="pt").input_ids
+output_ids = model.generate(input_ids)
+print(tokenizer.decode(output_ids[0], skip_special_tokens=True))
+#sample output
+#son model arabalar çevre için daha az zararlı mı?
+```
+#Cite
+```bibtex
+
+@inproceedings{bagci2021paraphrase,
+  title={Comparison of Turkish Paraphrase Generation Models},
+  author={Ba{\u{g}}c{\i}, Ahmet and Amasyali, Mehmet Fatih},
+  booktitle={2021 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)},
+  year={2021},
+  organization={IEEE}
+}
+```