DeepSpeed
What it is
DeepSpeed is a deep learning optimization library designed to make distributed training and inference of large-scale models efficient and easy. It employs techniques like ZeRO (Zero Redundancy Optimizer), 3D Parallelism, and various offloading engines to handle massive model parameters and training data.
The problem it solves
Memory bottlenecks and communication overhead during the training and inference of massive deep learning models.
What you could use it for
- Training Large Language Models (LLMs) with billions of parameters
- Distributed training and inference across multiple GPUs or nodes
- Efficient model training using ZeRO-Infinity or ZeRO-3 for memory optimization
- Large-scale model distillation and long-sequence training
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.