TPU-MLIR is a machine learning compiler built on MLIR that transforms pre-trained models from frameworks like PyTorch, ONNX, TFLite, and Caffe into efficient bmodel files for deployment on Sophgo TPUs. It provides a unified intermediate representation, a clean lowering pipeline, and tools for quantization and calibration to optimize model performance on hardware.