Machine learning library, Distributed training, Deep learning, Reinforcement learning, Models, TensorFlow, PyTorch

☄️ Parallel and distributed training with spaCy and Ray

Cross-lingual Language Model (XLM) pretraining and Model-Agnostic Meta-Learning (MAML) for fast adaptation of deep networks

A simple package for distributed model training using Distributed Data Parallel (DDP) in PyTorch.

Ring sliding window attention implementation with flash attention

This repository is a tutorial targeting how to train a deep neural network model in a higher efficient way. In this repository, we focus on two main frameworks that are Keras and Tensorflow.

Deep Q-Network (DQN) implementation for optimal maintenance planning of 100-bridge fleet infrastructure using advanced reinforcement learning techniques and vectorized parallel training.

Deep Q-Network implementation for optimal bridge maintenance planning using Markov Decision Process formulation with vectorized parallel training. Based on Phase 3 (Vectorized DQN) from dql-maintenance-faster project.

tic-tac-toe with q-learning

Nano-Qwen ⚡🧠 - A from-scratch implementation of a light weight Qwen-style transformer designed for clarity and experimentation. Includes an efficient Mixture-of-Experts (MoE) architecture, plus built-in support for parallel and distributed training to scale models from a minimal codebase.

Parallel hyperparameter tuning for Metaflow with true adaptive TPE — no sequential bottleneck