Update README.md

README.md

@@ -1,3 +1,49 @@
 ---
 license: mit
+language: en
+tags:
+
+- adverse-drug-events
+- twitter
+- social-media-mining-for-health
+- SMM4H
+
+widget:
+- text: "joints killing me now i have gone back up on the lamotrigine. sick of side effects. sick of meds. want my own self back. knackered today"
+  example_title: "Adverse Drug Event Detection - ADE"
+- text: "bout to have a kick ass summer then it's time to get serious fer school #vyvanse #geekmode"
+  example_title: "Adverse Drug Event Detection - noADE"
 ---
+
+## t2t-assert-ade-balanced
+
+t2t-assert-ade-balanced is a text-to-text (**t2t**) adverse drug event (**ade**) detection model trained with over- and undersampled (balanced) English tweets reporting adverse drug events. It is trained as part of BOUN-TABI system for the Social Media Mining for Health (SMM4H) 2022 shared task. The system description paper has been accepted for publication in *Proceedings of the Seventh Social Media Mining for Health (#SMM4H) Workshop and Shared Task* and will be available soon. The source code has been released on GitHub at [https://github.com/gokceuludogan/boun-tabi-smm4h22](https://github.com/gokceuludogan/boun-tabi-smm4h22).
+
+The model utilizes the T5 model and its text-to-text formulation. The inputs are fed to the model directly as a sentence/tweet, and receives the output "adverse event problem" or "healthy okay". 
+
+## Requirements
+```
+sentencepiece
+transformers
+```
+
+## Usage
+
+```python
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
+tokenizer = AutoTokenizer.from_pretrained("yirmibesogluz/t2t-assert-ade-balanced")
+model = AutoModelForSeq2SeqLM.from_pretrained("yirmibesogluz/t2t-assert-ade-balanced")
+predictor = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+predictor("joints killing me now i have gone back up on the lamotrigine. sick of side effects. sick of meds. want my own self back. knackered today")
+```
+
+## Citation
+
+```bibtex
+@inproceedings{uludogan-gokce-yirmibesoglu-zeynep-2022-boun-tabi-smm4h22,
+    title = "{BOUN}-{TABI}@{SMM4H}'22: Text-to-{T}ext {A}dverse {D}rug {E}vent {E}xtraction with {D}ata {B}alancing and {P}rompting",
+    author = "Uludo{\u{g}}an, G{\"{o}}k{\c{c}}e  and Yirmibe{\c{s}}o{\u{g}}lu, Zeynep",
+    booktitle = "Proceedings of the Seventh Social Media Mining for Health ({\#}SMM4H) Workshop and Shared Task",
+    year = "2022",
+}
+```