Ok verovatno finalni pull request

README.md

@@ -26,7 +26,12 @@ library_name: transformers
 # Zero and few shot NER for biomedical texts
 
 ## Model description
-Model takes as input two strings. String1 is NER label. String1 must be phrase for entity. String2 is short text where String1 is searched for semantically.
+
+This model was created during the research collaboration between Bayer Pharma and Serbian Institute for Artificial Intelligence Research and Development. 
+The model is trained on about 25+ biomedical NER classes and can perform also zero-shot inference and can be further fine-tuned for new classes with just few examples (few-shot learning). 
+For more details about our methods please see the paper named ["A transformer-based method for zero and few-shot biomedical named entity recognition"](https://arxiv.org/abs/2305.04928).
+
+Model takes as input two strings. String1 is NER label that is being searched in second string. String1 must be phrase for entity. String2 is short text where String1 is searched for semantically.
 model outputs list of zeros and ones corresponding to the occurance of Named Entity and corresponing to the tokens(tokens given by transformer tokenizer) of the Sring2.
 
 ## Example of usage
@@ -94,4 +99,20 @@ On top of this, one can use the model in zero-shot regime with other classes, an
 
 Code used for training and testing the model is available at https://github.com/br-ai-ns-institute/Zero-ShotNER 
 
-## Citation
+## Citation
+
+If you use this model, or are inspired by it, please cite in your paper the following paper: 
+
+Košprdić M.,Prodanović N., Ljajić A., Bašaragin B., Milošević N., 2023. A transformer-based method for zero and few-shot biomedical named entity recognition. arXiv preprint arXiv:2305.04928. https://arxiv.org/abs/2305.04928
+
+or in bibtex:
+```
+@misc{kosprdic2023transformerbased,
+      title={A transformer-based method for zero and few-shot biomedical named entity recognition}, 
+      author={Miloš Košprdić and Nikola Prodanović and Adela Ljajić and Bojana Bašaragin and Nikola Milošević},
+      year={2023},
+      eprint={2305.04928},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```