Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model
We introduce Xmodel-VLM, a cutting-edge multimodal vision language model. It
is designed for efficient deployment on consumer GPU servers. Our work directly
confronts a pivotal industry issue by grappling with the prohibitive service
costs that hinder the broad adoption of large-scale multimodal systems. Through
rigorous training, we have developed a 1B-scale language model from the ground
up, employing the LLaVA paradigm for modal alignment. The result, which we call
Xmodel-VLM, is a lightweight yet powerful multimodal vision language model.
Extensive testing across numerous classic multimodal benchmarks has revealed
that despite its smaller size and faster execution, Xmodel-VLM delivers
performance comparable to that of larger models. Our model checkpoints and code
are publicly available on GitHub at https://github.com/XiaoduoAILab/XmodelVLM.
6645640e7317f54c0de88f74
Wanting Xu
admin_assigned
2024-05-16T12:37:05.444Z
6526c16310184f8350667bce
/avatars/afc44d1efe58ce0765bbabbfaf9a1b4b.svg
Xu
user
wantingXu
6645640e7317f54c0de88f75
Yang Liu
6645640e7317f54c0de88f76
Langping He
6645640e7317f54c0de88f77
Xucheng Huang
admin_assigned
2024-05-16T12:37:27.085Z
637dda5b976326508039b2e9
/avatars/e5bbc245cef4ff5ca3f9e1ab28bb8b87.svg
Xucheng Huang
user
hxc123china
6645640e7317f54c0de88f78
Ling Jiang
Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model
We introduce Xmodel-VLM, a cutting-edge multimodal vision language model. It
is designed for efficient deployment on consumer GPU servers. Our work directly
confronts a pivotal industry issue by grappling with the prohibitive service
costs that hinder the broad adoption of large-scale multimodal systems. Through
rigorous training, we have developed a 1B-scale language model from the ground
up, employing the LLaVA paradigm for modal alignment. The result, which we call
Xmodel-VLM, is a lightweight yet powerful multimodal vision language model.
Extensive testing across numerous classic multimodal benchmarks has revealed
that despite its smaller size and faster execution, Xmodel-VLM delivers
performance comparable to that of larger models. Our model checkpoints and code
are publicly available on GitHub at https://github.com/XiaoduoAILab/XmodelVLM.
Xmodel-VLM is a lightweight multimodal vision language model developed for efficient deployment, achieving performance comparable to larger models with a 1B language model trained using the LLaVA paradigm.
multimodal vision language model consumer GPU servers service costs 1B-scale language model LLaVA paradigm modal alignment multimodal benchmarks