MobileVLM : A Fast, Reproducible and Strong Vision Language Assistant for Mobile Devices
Paper • 2312.16886 • Published • 22
Model Summery
MobileVLM is a competent multimodal vision language model (MMVLM) targeted to run on mobile devices. It is an amalgamation of a myriad of architectural designs and techniques that are mobile-oriented, which comprises a set of language models at the scale of 1.4B and 2.7B parameters, trained from scratch, a multimodal vision model that is pre-trained in the CLIP fashion, cross-modality interaction via an efficient projector. We evaluate MobileVLM on several typical VLM benchmarks. Our models demonstrate on par performance compared with a few much larger models. More importantly, we measure the inference speed on both a Qualcomm Snapdragon 888 CPU and an NVIDIA Jeston Orin GPU, and we obtain state-of-the-art performance of 21.5 tokens and 65.3 tokens per second, respectively.
The MobileVLM-1.7B was built on our MobileLLaMA-1.4B-Chat to facilitate the off-the-shelf deployment.
Model Sources
- Repository: https://github.com/Meituan-AutoML/MobileVLM
- Paper: https://arxiv.org/abs/2312.16886
How to Get Started with the Model
Inference examples can be found at Github.
Training Details
Please refer to our paper: MobileVLM: A Fast, Strong and Open Vision Language Assistant for Mobile Devices
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Install from pip and serve model
# Install vLLM from pip: pip install vllm# Start the vLLM server: vllm serve "mtgv/MobileVLM-1.7B"# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mtgv/MobileVLM-1.7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'