超越 FP16 + ONNX 優化 Transformer 模型大小與推論效能（剪枝/圖形最佳化幫助有限）

Hi everyone, I’ve been working on optimizing a transformer-based neural network for both inference speed and model size, but I feel like I’ve hit a plateau and would appreciate some guidance. So far I’ve converted weights to FP16 (about 2× size reduction), exported and optimized with ONNX Runtime for inference speed, and tried both unstructured and structured pruning as well as ONNX graph optimizations, but none of these gave significant additional gains, and I’m still around ~162 MB per model.