Update README.md

README.md

@@ -5,8 +5,16 @@ license: bsd-3-clause
 # ProCALM
 [ProCALM](https://github.com/jsunn-y/ProCALM/tree/main) (Protein Conditionally Adapted Language Model) is a suite of models where [ProGen2-base](https://github.com/enijkamp/progen2) is finetuned with conditional adapters for conditional generation of functional enzymes, based on EC number, taxonomy, or both.
 
-ProCALM models share `tokenizer.json` but each model is organized into subfolders.
-
+ProCALM models share `tokenizer.json` and individual models are organized into subfolders. We have uploaded the most relevant models here, but please reach out if you would like to use other models from our paper. `1.5B` and `9B` refer to checkpoints trained to 1.5 and 9 billion tokens, respectively
 
+| Name | Description |
+|:--------|:-------:|
+| progen2-base | Original ProGen2 model with ~760 million parameters|
+| ec-onehot-uniref | Trained with onehot-encoded EC conditioning, on ~29e6 enzymes from Uniref |
+| ec-onehot-swissprot | Trained with onehot-encoded EC conditioning, on ~150e3 enzymes from Swissprot Train |
+| tax-swissprot | Trained on onehot-encoded EC taxonomy conditioning, on ~150e3 enzymes from Swissprot Train |
+| ec+tax-swissprot | Trained jointly on onehot-encoded EC conditioning and onehot-encoded taxonomy conditioning with parallel adapters, on ~150e3 enzymes from Swissprot Train |
+| ec-drfp-swissprot | Trained with DRFP-encoded EC conditioning, on ~150e3 enzymes from Swissprot Train |
+| ec-creep-swissprot | Trained with CREEP-encoded EC conditioning, on ~150e3 enzymes from Swissprot Train |
 
 More usage details can be found in [github](https://github.com/jsunn-y/ProCALM/tree/main) and in our paper.