PKUWZP/DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
CS and Statistics PhD graduate with research interests in ML Systems, Computer Vision, Multimodal LLMs and Statistical Learning.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Example models using DeepSpeed
SGLang is a high-performance serving framework for large language models and multimodal models.
Enabling PyTorch on XLA Devices (e.g. Google TPU)
Datasets, Transforms and Models specific to Computer Vision
Tensors and Dynamic neural networks in Python with strong GPU acceleration
🍕 This is a project to identify your next open source contribution.
MiniCPM3-4B: An edge-side LLM that surpasses GPT-3.5-Turbo.
Implementation of PALI3 from the paper PALI-3 VISION LANGUAGE MODELS: SMALLER, FASTER, STRONGER"
Denoising Diffusion Implicit Models
Deep Learning with Ensemble Methods
R Package for Regression with Partial Differential Regularizations, using the Finite Element Method
We investigate the effect of populations on finding good solutions to the robust MDP
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
A Configurable Recommender Systems Simulation Platform
A comparison of Google SlateQ algorithm with traditional Reinforcement Learning algorithms
Python Multi-Agent Reinforcement Learning framework
Stochastic Simulations of Gene Regulatory Networks
Sampling profiler for Python programs
dynamic sliding window for text categorization using LSTM
NLP collaborative Project between Zhipeng and Ming
A Swiss-Army Knife for Data I/O
R Packages for Markdown templates