DeepSeek-OCR and the Unreasonable Usefulness of Compression

This post details the deployment of the DeepSeek-OCR model on Baseten, focusing on the practical aspects of packaging and serving a highly compressed visual model. It highlights the use of Truss for model deployment, including specific `config.yaml` configurations for dependencies (vLLM, flash-attn) and resource allocation (H100_40GB). The post also touches on debugging build commands by examining deployment logs and referencing base images. The core technical contribution is demonstrating how to achieve performant inference for a model that leverages compression for efficiency, enabling applications like scalable training data generation, near-infinite context windows, and real-time computer-use agents.