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---
license: apache-2.0
---
# LMDrive Model Card
## Model details
**Model type:**
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.
The model weight is for the vision encoder used in the LMDrive.
**Model date:**
LMDrive-1.0 was trained in November 2023.
**Paper or resources for more information:**
Github: https://github.com/opendilab/LMDrive/README.md
Paper: https://arxiv.org/abs/2312.07488
**Where to send questions or comments about the model:**
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
## Evaluation benchmark
LangAuto, LangAuto-short, LangAuto-tiny, LangAuto-notice |