The RUN Pipeline trains, evaluates, and tests two convolutional neural network models used to detect strong lensing in images. The code first classifies strong lenses from non-lenses with a ResNet model, and further detects the locations of small Einstein radius systems in cutout images down to θ_E∼0.03″ with a U-Net model. After both models are trained, the software analyzes the performance of the pipeline on validation and testing data.