Model type: SESAME is an open-source multimodal model trained by fine-tuning LLaVA on various instruction-based image grounding (segmentation) data. It is an auto-regressive language model plus a segmentation model.
Primary intended uses: The primary use of SESAME is research on large multimodal models and chatbots.
Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
Training dataset: (FP-/R-)RefCOCO(+/g) + LLaVA 150K VQA data
