# Model Summery
We propose Lenna a Language enhanced reasoning detection assistant, which utilizes the robust multimodal feature representation of MLLMs, while preserving location information for detection. 
This is achieved by incorporating an additional <DET> token in the MLLM vocabulary that is free of explicit semantic context but serves as a prompt for the detector to identify the corresponding position. 
To evaluate the reasoning capability of Lenna, we construct a ReasonDet dataset to measure its performance on reasoning-based detection.

# Model Sources
- Repository: https://github.com/Meituan-AutoML/Lenna
- Paper: https://arxiv.org/abs/2312.02433

# How to Get Started with the Model
Model weights can be loaded with Hugging Face Transformers. Examples can be found at [Github](https://github.com/Meituan-AutoML/Lenna).
{"language": ["en"], "license": "apache-2.0", "datasets": ["liuhaotian/LLaVA-Instruct-150K", "jxu124/refcoco", "jxu124/refcocog", "jxu124/refcocoplus"], "metrics": ["accuracy"]}
transformers pytorch llava text-generation en dataset:liuhaotian/LLaVA-Instruct-150K dataset:jxu124/refcoco dataset:jxu124/refcocog dataset:jxu124/refcocoplus arxiv:2312.02433 license:apache-2.0 autotrain_compatible endpoints_compatible region:us