update readme

Author: liugangcode

README.md

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 `torch-molecule` is a package under active development that facilitates molecular discovery through deep learning, featuring a user-friendly, `sklearn`-style interface. It includes model checkpoints for efficient deployment and benchmarking across a range of molecular tasks. Currently, the package focuses on three main components:
 
-1. **Predictive Models**: Done: GREA, SGIR, IRM, GIN/GCN w/ virtual, DIR. TODO: SMILES-based LSTM/Transformers, more
-2. **Generative Models**: Done: Graph DiT, GraphGA, DiGress. TODO:, GDSS, more
+1. **Predictive Models**: Done: GREA, SGIR, IRM, GIN/GCN w/ virtual, DIR. SMILES-based LSTM/Transformers. TODO more
+2. **Generative Models**: Done: Graph DiT, GraphGA, DiGress, GDS, MolGPT TODO: more
 3. **Representation Models**: Done: MoAMa, AttrMasking, ContextPred, EdgePred. Many pretrained models from HF. TODO: checkpoints, more 
 
 see the [List of Supported Models](#list-of-supported-models) section.