DeepSpeed Compression: A composable library for extreme
Large-scale models are revolutionizing deep learning and AI research, driving major improvements in language understanding, generating creative texts, multi-lingual translation and many more. But despite their remarkable capabilities, the models’ large size creates latency and cost constraints that hinder the deployment of applications on top of them. In particular, increased inference time and memory consumption […]
ZeRO-Infinity and DeepSpeed: Unlocking unprecedented model scale for deep learning training - Microsoft Research
GitHub - microsoft/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
This AI newsletter is all you need #6
Shaden Smith on LinkedIn: DeepSpeed Data Efficiency: A composable library that makes better use of…
GitHub - microsoft/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
ZeroQuant与SmoothQuant量化总结-CSDN博客
DeepSpeed Compression: A composable library for extreme compression and zero-cost quantization - Microsoft Research
Microsoft AI Releases 'DeepSpeed Compression': A Python-based Composable Library for Extreme Compression and Zero-Cost Quantization to Make Deep Learning Model Size Smaller and Inference Speed Faster - MarkTechPost
This AI newsletter is all you need #6, by Towards AI Editorial Team
DeepSpeed: Advancing MoE inference and training to power next-generation AI scale - Microsoft Research
This AI newsletter is all you need #6
This AI newsletter is all you need #6 – Towards AI
PDF) DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing
DeepSpeed ZeRO++: A leap in speed for LLM and chat model training with 4X less communication - Microsoft Research
DeepSpeed Compression: A composable library for extreme compression and zero-cost quantization - Microsoft Research
