Developed and integrated LFM2-VL multimodal input support for the GRPO and RLOO trainers in the huggingface/trl repository, enabling these trainers to process and manage spatial shapes and tile-indexed tensors. This feature expanded the trainers’ capabilities for multimodal deep learning experiments, allowing for richer data processing and potentially improved model accuracy. The work involved end-to-end implementation using Python and PyTorch, with a focus on robust data processing and seamless integration into existing training workflows. Collaboration with other contributors ensured code quality and smooth adoption. No major bugs were reported or addressed during this period, reflecting a focused feature delivery.