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README.md
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---
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license: apache-2.0
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---
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# LMDrive Model Card
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## Model details
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**Model type:**
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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.
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The model weight is for the vision encoder used in the LMDrive.
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**Model date:**
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LMDrive-1.0 was trained in November 2023.
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**Paper or resources for more information:**
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Github: https://github.com/opendilab/LMDrive/README.md
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Paper: https://arxiv.org/abs/2312.07488
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**Where to send questions or comments about the model:**
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https://github.com/opendilab/LMDrive/issues
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## Intended use
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**Primary intended uses:**
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The primary use of LMDrive is research on large multimodal models for autonomous driving.
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**Primary intended users:**
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The primary intended users of the model are researchers and hobbyists in computer vision, large multimodal model, autonomous driving, and artificial intelligence.
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## Training dataset
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- 64K instruction-sensor-control data clips collected in the CARLA simulator. [dataset_webpage](https://huggingface.co/datasets/deepcs233/LMDrive)
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- 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
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## Evaluation benchmark
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LangAuto, LangAuto-short, LangAuto-tiny, LangAuto-notice
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