Update README.md

README.md

@@ -8,7 +8,7 @@ tags:
 - biology
 ---
 Chemlactica-125m is a continually pretrained [galactica-125m](https://huggingface.co/facebook/galactica-125m) model for organic molecules. 
-It is pretrained on (soon-to-be-released) 40B tokens covering 110M+ molecules from PubChem as well as their chemical properties 
+It is pretrained on [40B tokens covering 110M+ molecules from PubChem](https://huggingface.co/datasets/yerevann/PubChemForLM) as well as their chemical properties 
 (molecular weight, synthetic accessibility score, drug-likeness etc.) 
 and similarities (Tanimoto distance between ECFP fingerprints).
 
@@ -19,10 +19,10 @@ Example prompts:
 `</s>[SAS]2.25[/SAS][SIMILAR]0.62 CC(=O)OC1=CC=CC=C1C(=O)O[/SIMILAR][START_SMILES]` will attempt to generate a molecule that has 2.25 SAS score and 
 has a 0.62 similarity score to the given molecule.
 
-The model can be wrapped into an optimization loop to traverse the chemical space with evolving prompts. 
+The model can be wrapped into an optimization loop to traverse the chemical space with evolving prompts. See the [code on GitHub](https://github.com/YerevaNN/ChemLactica). 
 
-A preprint with the details of the model and an optimization algorithm built on top of this model that sets state-of-the-art on Practical Molecular Optimization 
-and other benchmarks will be released soon.
+A preprint with the details of the model and an optimization algorithm built on top of this model that sets state-of-the-art on 
+Practical Molecular Optimization and other benchmarks is [available on arxiv](https://arxiv.org/abs/2407.18897).
 
 Few notes:
 * All queries should start with `</s>` symbol.