Projects
Here's a collection of my open-source contributions and technical projects.
Axolotl
Implemented optimizations and algorithms for Axolotl, a popular open-source LLM post-training library, improving model performance and efficiency.
BindsNET
A PyTorch-based spiking neural networks simulation library, specifically designed for machine learning applications. It allows researchers to quickly build complex spiking network models and train them using various learning rules.
LM-SNN
Unsupervised handwritten digit classification using spiking neural networks and spike-timing-dependent plasticity. Built on Peter Diehl's research work at ETH Zurich, with convolutional network extensions developed at UMass Amherst's BINDS laboratory.
GitHub Repository →AWR (Advantage-Weighted Regression)
Reference implementation of Advantage-Weighted Regression with TensorFlow 2.0 and Pyoneer. Based on the paper by Peng et al., providing a simple and scalable approach to off-policy reinforcement learning.
GitHub Repository →Open Source Contributions
If you're interested in collaborating, please reach out!
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