At Chandar Lab, we are happy to announce the third edition of our assistance program to provide feedback for members of communities underrepresented in AI who want to apply to high-profile graduate programs. Want feedback? Details: chandar-lab.github.io/grad_app/. Deadline: Nov 01!
We just made NovoMolGen easy to play with: Transformers-native checkpoints on the Hub and small notebooks that let you load, sample, and fine-tune in minutes. The few lines of code that load the model, plug in a reward, run a short RL finetune, and plot the curve.
Want to generate molecules immediately? Use the Transformers-native checkpoint. It loads with AutoModelForCausalLM and works with .generate() (no custom code required). Model card + example: huggingface.co/chandar-lab/...
For more context, design choices, scaling observations, and practical tips for applying NovoMolGen to new tasks see our blogpost:
chandar-lab.github.io/NovoMolGen/
I am recruiting several graduate students (both MSc and PhD level) for Fall 2026! The application deadline is December 01. Please apply through the Mila supervision request process here: mila.quebec/en/prospecti....
More details about the recruitment process here: chandar-lab.github.io/join/
To reproduce our unconstrained results, the quickstart notebook samples 30k SMILES and computes the six metrics from our table (Validity, Unique@1k, IntDiv, FCD, SNN, Frag/Scaf) in one cell.
github.com/chandar-lab/...
To optimize for your own objective, start with this finetuning notebook. It defines a reward (via MoleculeEvaluator or your function), builds our AugmentedHC trainer, and runs a short loop so you can see “before vs after” quickly.
github.com/chandar-lab/...
Sarath Chandar
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
