BayesAdapt

BayesAdapt is a library for the Bayesian adaptation of LLMs.

It also acts as the official repo for:
Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference
Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha
Conference on Uncertainty in Artificial Intelligence, 2025
[📄 Paper] [🌐 OpenReview]

⚙️ Installation

BayesAdapt uses uv to manage requirements. Start by installing uv as described by the official documentation.

Clone the code by running: git clone https://github.com/SRI-CSL/BayesAdapt.git

Inside the BayesAdapt/ directory run uv init to build the environment.

Then run source .venv/bin/activate to load the environment.

To use wandb, make sure the environment variable WANDB_ENTITY is set to your full wandb username.

🚀 Running the Code

TODO

📚 Citation

@InProceedings{samplawski2025scalable,
  title={Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference},
  author={Samplawski, Colin and Cobb, Adam D and Acharya, Manoj and Kaur, Ramneet and Jha, Susmit},
  booktitle={Conference on Uncertainty in Artificial Intelligence},
  year={2025}
}