Accelerate PyTorch with DeepSpeed to train large language models with Intel Habana Gaudi-based DL1 EC2 instances
Training large language models (LLMs) with billions of parameters can be challenging. In addition to designing the model architecture, researchers need to set up state-of-the-art training techniques for distributed training like mixed precision support, gradient accumulation, and checkpointing. With large models, the training setup is even more challenging because the available memory in a single …