AIMET provides post-training and quantization-aware fine-tuning techniques to minimize accuracy loss when compressing deep learning models. It supports models from ONNX and PyTorch frameworks and is designed to facilitate efficient deployment on resource-constrained edge devices like mobile phones and laptops.