This paper introduces SEMODS, a dataset of 3,427 software engineering (SE) models extracted and validated from Hugging Face. It aims to bridge the gap in identifying SE-specific models for AI integration by linking them to SE tasks, standardizing evaluation results, and supporting various applications like model discovery and benchmarking.