|
--- |
|
license: apache-2.0 |
|
tags: |
|
- MobileVLM |
|
--- |
|
## 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-3B was built on our [MobileLLaMA-2.7B-Chat](https://huggingface.co/mtgv/MobileLLaMA-2.7B-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](https://github.com/Meituan-AutoML/MobileVLM). |
|
|
|
## Training Details |
|
Please refer to our paper: [MobileVLM: A Fast, Strong and Open Vision Language Assistant for Mobile Devices](https://arxiv.org/pdf/2312.16886.pdf) |
|
|
