Update README.md

README.md

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 license: mit
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-HalDet-LLaVA is designed for multimodal hallucination detection, trained on the MHaluBench training dataset, achieving detection performance close to that of using GPT4-Vision.
+## HalDet-LLaVA
+
+HalDet-LLaVA is designed for multimodal hallucination detection, trained on the MHaluBench training dataset, achieving detection performance close to that of using GPT4-Vision.
+
+HalDet-LLaVA is trained on the [MHaluBench training set](https://huggingface.co/datasets/openkg/MHaluBench/blob/main/MHaluBench_train.json) using LLaVA-v1.5, specific parameters can be found in the file [finetune_task_lora.sh](https://github.com/zjunlp/EasyDetect/blob/main/HalDet-LLaVA/finetune_task_lora.sh).
+
+We trained HalDet-LLaVA on 1-A800 in 1 hour. If you don"t have enough GPU resources, we will soon provide model distributed training scripts.
+
+You can inference our HalDet-LLaVA by using [inference.py](https://github.com/zjunlp/EasyDetect/blob/main/HalDet-LLaVA/inference.py)
+
+To view more detailed information about HalDet-LLaVA and the train dataset, please refer to the [EasyDetect](https://github.com/zjunlp/EasyDetect) and [readme](https://github.com/zjunlp/EasyDetect/blob/main/HalDet-LLaVA/README.md)