Update README.md

README.md

@@ -10,28 +10,35 @@ license: apache-2.0
 LMDrive is an end-to-end, closed-loop, language-based autonomous driving framework, which interacts with the dynamic environment via multi-modal multi-view sensor data and natural language instructions.
 
 **Model date:**
-LMDrive-1.0 (based on LLaVA-v1.5-7B) was trained in November 2023.
+LMDrive-1.0 (based on LLaVA-v1.5-7B) was trained in November 2023. The original LLaVA-v1.5 also needs to be downloaded.
 
 **Paper or resources for more information:**
+
 Github: https://github.com/opendilab/LMDrive/README.md
 
 Paper: https://arxiv.org/abs/2312.07488
 
 **Related weights for the vision encoder**
+
 https://huggingface.co/deepcs233/LMDrive-vision-encoder-r50-v1.0
 
 **Where to send questions or comments about the model:**
-https://github.com/haotian-liu/LLaVA/issues
+
+https://github.com/opendilab/LMDrive/issues
+
 
 
 ## Intended use
 **Primary intended uses:**
+
 The primary use of LMDrive is research on large multimodal models for autonomous driving.
 
 **Primary intended users:**
+
 The primary intended users of the model are researchers and hobbyists in computer vision, large multimodal model, autonomous driving, and artificial intelligence.
 
 ## Training dataset
+
 - 64K instruction-sensor-control data clips collected in the CARLA simulator. [dataset_webpage](https://huggingface.co/datasets/deepcs233/LMDrive)
   - where each clip includes one navigation instruction, several notice instructions, a sequence of multi-modal multi-view sensor data, and control signals. The duration of the clip spans from 2 to 20 seconds