Fine-tuning and applying MIST (Molecular Insight SMILES Transformer) foundation models to chemical problems.
Jupyter Notebook
4
404 commits
updated Jul 11, 2026
This repository contains tutorials for fine-tuning and applying MIST (Molecular Insight SMILES Transformer) foundation models to chemical problems.
Model checkpoints for MIST models are available on HuggingFace and on Zenodo.
The full code, including pre-training, model development and full scale application demos can be found in the mist repository.
Inference demonstrations using fine-tuned MIST models:
Complete fine-tuning workflow for MIST encoder models:
Exploring how molecules smell with the MIST olfaction model:
git clone <repository-url>
cd mist-demo
uv sync
source .venv/bin/activate # On Windows: .venv\Scripts\activate
Launch Jupyter and open any notebook in mist-demo/tutorials:
jupyter notebook
If you use the MIST models in your work please cite:
@online{MIST,
title = {Foundation Models for Discovery and Exploration in Chemical Space},
author = {Wadell, Alexius and Bhutani, Anoushka and Azumah, Victor and Ellis-Mohr, Austin R. and Kelly, Celia and Zhao, Hancheng and Nayak, Anuj K. and Hegazy, Kareem and Brace, Alexander and Lin, Hongyi and Emani, Murali and Vishwanath, Venkatram and Gering, Kevin and Alkan, Melisa and Gibbs, Tom and Wells, Jack and Varshney, Lav R. and Ramsundar, Bharath and Duraisamy, Karthik and Mahoney, Michael W. and Ramanathan, Arvind and Viswanathan, Venkatasubramanian},
date = {2025-10-20},
eprint = {2510.18900},
eprinttype = {arXiv},
eprintclass = {physics},
doi = {10.48550/arXiv.2510.18900},
url = {http://arxiv.org/abs/2510.18900},
Fine-tuning and applying MIST (Molecular Insight SMILES Transformer) foundation models to chemical problems.
Jupyter Notebook
4
404 commits
updated Jul 11, 2026
This repository contains tutorials for fine-tuning and applying MIST (Molecular Insight SMILES Transformer) foundation models to chemical problems.
Model checkpoints for MIST models are available on HuggingFace and on Zenodo.
The full code, including pre-training, model development and full scale application demos can be found in the mist repository.
Inference demonstrations using fine-tuned MIST models:
Complete fine-tuning workflow for MIST encoder models:
Exploring how molecules smell with the MIST olfaction model:
git clone <repository-url>
cd mist-demo
uv sync
source .venv/bin/activate # On Windows: .venv\Scripts\activate
Launch Jupyter and open any notebook in mist-demo/tutorials:
jupyter notebook
If you use the MIST models in your work please cite:
@online{MIST,
title = {Foundation Models for Discovery and Exploration in Chemical Space},
author = {Wadell, Alexius and Bhutani, Anoushka and Azumah, Victor and Ellis-Mohr, Austin R. and Kelly, Celia and Zhao, Hancheng and Nayak, Anuj K. and Hegazy, Kareem and Brace, Alexander and Lin, Hongyi and Emani, Murali and Vishwanath, Venkatram and Gering, Kevin and Alkan, Melisa and Gibbs, Tom and Wells, Jack and Varshney, Lav R. and Ramsundar, Bharath and Duraisamy, Karthik and Mahoney, Michael W. and Ramanathan, Arvind and Viswanathan, Venkatasubramanian},
date = {2025-10-20},
eprint = {2510.18900},
eprinttype = {arXiv},
eprintclass = {physics},
doi = {10.48550/arXiv.2510.18900},
url = {http://arxiv.org/abs/2510.18900},