Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Python Implementation of Reinforcement Learning: An Introduction

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.

Python library that makes it easy for data scientists to create charts.

Ongoing research training transformer language models at scale, including: BERT & GPT-2

Intel PMU profiling tools

A fast MoE impl for PyTorch

Reference implementations of MLPerf® inference benchmarks

FedScale is a scalable and extensible open-source federated learning (FL) platform.

An interference-aware scheduler for fine-grained GPU sharing

Artifact of OSDI '24 paper, ”Llumnix: Dynamic Scheduling for Large Language Model Serving“

ATC23 AE

Compiler for Dynamic Neural Networks

A Deep Learning Cluster Scheduler

Official repository for the paper DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines

Custom Python Scheduler for Kubernetes

A Quasi-Wasserstein Loss for Learning Graph Neural Networks (QW loss)