Update README.md

README.md

@@ -25,6 +25,16 @@ The model was trained using [Moritz Laurer's](https://huggingface.co/MoritzLaure
 
 The PolNLI dataset contains documents from social media, news outlets, congressional bills, court case summaries, and more. Classification should work well across a broad set of document sources and subjects, but for best performance refer to the recommendations section.
 
+If you use this model or the PolNLI data set please cite:
+```
+@article{burnham2024debate,
+  title={Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Text},
+  author={Burnham, Michael, Kayla Kahn, Rachel Peng, Ryan Wang},
+  journal={working manuscript},
+  year={2024}
+}
+```
+
 # Using NLI Classifiers
 NLI classifiers work by pairing a document (AKA the 'premise') with a 'hypothesis', and determining if the hypothesis is true given the content of the document. The hypothesis is supplied by the user and can be thought of as a simplified version of a prompt for an LLM. It's best to keep hypotheses short and simple with a single classification criteria. If a more complicated hypothesis is necessary, consider few-shot training.
 For more detailed reading on using NLI classifiers see: 
@@ -58,16 +68,4 @@ Evaluation is primarily conducted on the PolNLI test set. No hypotheses in the P
 <img src="https://cdn-uploads.huggingface.co/production/uploads/64d0341901931c60161f2a06/kDZXC-OsZtmTCxq0HsJMg.png" width="750" height="500"  />
 
 ### Few-shot performance vs. and Electra classifier trained on 2,000 documents:
-<img src="https://cdn-uploads.huggingface.co/production/uploads/64d0341901931c60161f2a06/WpQ_ZofMJMFPraCK_a3Fb.png" width="750" height="500"  />
-
-
-# Citation
-If you use this model or the PolNLI data set please cite:
-```
-@article{burnham2024debate,
-  title={Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Text},
-  author={Burnham, Michael, Kayla Kahn, Rachel Peng, Ryan Wang},
-  journal={working manuscript},
-  year={2024}
-}
-```
+<img src="https://cdn-uploads.huggingface.co/production/uploads/64d0341901931c60161f2a06/WpQ_ZofMJMFPraCK_a3Fb.png" width="750" height="500"  />