Getting Started with PyTorch BERT Models - Cerebras

This post details how to run PyTorch BERT models on Cerebras CS-2 systems. It introduces convenience wrappers in the Cerebras Software Platform (CSoft) for porting existing PyTorch scripts with minimal code changes. Key performance optimizations include multi-worker coordination for data loading and step closures for queuing functions between training iterations. A reference implementation of BERT in PyTorch is provided, including model, dataloader, and configuration YAMLs for BERTBASE and BERTLARGE variants. It outlines the process for running training and evaluation on CPU, compiling for WSE, and executing on a CS system using provided scripts.