MLIR is a key technology in modern ML compilers, but beginners often struggle with a common question: How do I import my neural network into MLIR’s upstream dialects? This talk provides a practical introduction to model import workflows, covering TensorFlow Lite to TOSA, PyTorch to MLIR via Torch-MLIR and torch.export, ONNX to MLIR using ONNX-MLIR and Torch-MLIR, and a brief discussion on JAX. Designed for newcomers, this session will walk through concrete examples to help lower the barrier to entry and clarify how ML models connect to MLIR’s ecosystem.