Update README.md

README.md

@@ -18,7 +18,6 @@ base_model:
 # ChemSolubilityBERTa
 ## Model Description
 ChemSolubilityBERTa is a prototype designed to predict the aqueous solubility of chemical compounds from their SMILES representations. Based on ChemBERTa, a BERT-like transformer-based architecture, ChemBERTa pre-trained on 77M SMILES strings for molecular property prediction. We adapted ChemBERTa to predict solubility values by fine-tuning ChemBERTa with the ESOL (Estimated SOLubility) dataset, a water solubility prediction dataset of 1,128 samples. A user inputs a SMILES string, and the model outputs a log solubility value (log mol/L).
-
 You can read the full paper [here](./01_ChemSolubilityBERTa.pdf).
 
 ## Fine-Tuning Details
@@ -42,9 +41,17 @@ inputs = tokenizer(smiles_string, return_tensors='pt')
 outputs = model(**inputs)
 solubility = outputs.logits.item()
 print(f"Predicted solubility: {solubility}")
+```
+## Citation and Usage
 
-##How to Use
-
-This model is licensed under the [MIT License](https://opensource.org/licenses/MIT).
+If you use ChemSolubilityBERTa in your research or projects, please cite the following:
 
+@misc{ChemSolubilityBERTa,
+  author = {Farooq Khan},
+  title = {ChemSolubilityBERTa: A Transformer-Based Model for Predicting Aqueous Solubility from SMILES},
+  year = {2024},
+  url = {https://huggingface.co/khanfs/ChemSolubilityBERTa}
+}
 
+## License
+This model is licensed under the [MIT License](https://opensource.org/licenses/MIT).