Update README.md

README.md

@@ -14,7 +14,7 @@ metrics:
 # CELL-E 2
 
 ## Model description
-[![CELL-E_2](images/architecture.png)](https://github.com/BoHuangLab/CELL-E_2)
+[![CELL-E_2](images/architecture.png)](https://bohuanglab.github.io/CELL-E_2/)
 
 CELL-E 2 is the second iteration of the original [CELL-E](https://www.biorxiv.org/content/10.1101/2022.05.27.493774v1) model which utilizes an amino acid sequence and nucleus image to make predictions of subcellular protein localization with respect to the nucleus.
 
@@ -68,6 +68,7 @@ These models were used the HPA models as checkpoints, but then were finetuned on
 | [`HPA_1280`](https://huggingface.co/HuangLab/CELL-E_2_HPA_Finetuned_1280) | 10.8 GB | |
 | [`HPA_2560`](https://huggingface.co/HuangLab/CELL-E_2_HPA_Finetuned_2560) | 17.5 GB | |
 
+To reduce download size, we removed the ESM-2 model from the checkpoint. This should be downloaded the first time the code is run, but is otherwise something to be aware of if loading into other projects.
 
 ### How to use
 
@@ -85,12 +86,13 @@ model.sample(text=sequence, condition=nucleus)
 ### BibTeX entry and citation info
 
 ```bibtex
-@article{,
-  author    = {Emaad Khwaja and
-                Yun S Song and
-                Aaron Agarunov and
-                Bo Huang},
-  title     = {{CELL-E 2:} Translating Proteins to Pictures and Back with a Bidirectional Text-to-Image Transforme},
+@inproceedings{
+anonymous2023translating,
+title={CELL-E 2: Translating Proteins to Pictures and Back with a Bidirectional Text-to-Image Transformer},
+author={Emaad Khwaja, Yun S. Song, Aaron Agarunov, and Bo Huang},
+booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
+year={2023},
+url={https://openreview.net/forum?id=YSMLVffl5u}
 }
 ```