Accelerate BERT inference with DeepSpeed-Inference on GPUs

A hands-on tutorial demonstrating how to optimize BERT-large for GPU inference using DeepSpeed-Inference with minimal code changes. Using a fine-tuned NER model on CoNLL-2003, the guide walks through setting up the environment, establishing a baseline, applying DeepSpeed's InferenceEngine via a single `deepspeed.init_inference` call, and benchmarking results. The optimization reduces latency from 30.4ms to 10.4ms (2.92x speedup) while retaining 99.88% of the original model accuracy on an NVIDIA T4 GPU.