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README.md

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 license: mit
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-SESAME Model Card
-
-Model details
-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.
-
-Paper or resources for more information: https://see-say-segment.github.io/
-
-Where to send questions or comments about the model: https://github.com/see-say-segment/sesame/issues
-
-Intended use
-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
+## SESAME
+
+- 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.
+- Paper or resources for more information: https://see-say-segment.github.io/
+- Where to send questions or comments about the model: https://github.com/see-say-segment/sesame/issues
+- Intended use
+  - 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