huggingface-accelerate

Distributed training across multiple GPUs requires minimal code changes when using a unified API that handles device placement and mixed precision automatically. You can launch a single script across single or multi-GPU environments using the accelerate launch command.

Switching between FSDP and DeepSpeed for scalable model training is streamlined by using a single unified API. This approach abstracts backend-specific logic, allowing you to configure various parallelism strategies without rewriting your core training script.

Yes, accelerate supports multi-node training with mixed precision. It provides automatic device and mixed-precision handling, allowing you to deploy scalable training jobs across multi-node clusters seamlessly through interactive configuration.

Yes, the unified API supports Megatron-LM parallelism strategies. It is designed to integrate multiple backends including DDP, DeepSpeed, FSDP, and Megatron-LM, enabling scalable training across diverse hardware configurations.

Yes, you need torch and transformers installed alongside accelerate to use this distributed training approach. These dependencies are required to satisfy the runtime instructions and execute the unified API across your hardware.

Using a single script for distributed training eliminates the complexity of maintaining backend-specific implementations. It unifies the workflow for DDP, DeepSpeed, FSDP, and Megatron-LM, ensuring seamless model preparation and scalable training with minimal code changes.