MMMModal -- Multi-Images Multi-Audio Multi-turn Multi-Modal
Husein Zolkepli Aisyah Razak Kamarul Adha Ariff Nazhan
Our contribution introduces a groundbreaking multimodal large language model
designed to comprehend multi-images, multi-audio, and multi-images-multi-audio
within a single multiturn session. Leveraging state-of-the-art models, we
utilize the SigLIP encoder for visual inputs and the Whisper Encoder for audio
inputs. Notably, this multimodal large language model is bilingual, proficient
in understanding both English and Malay simultaneously. We proudly unveil two
versions of this model: TinyLlama with 1.1B parameters, and Mistral with 7B
parameters. With its ability to navigate diverse modalities and languages, our
model represents a significant advancement for the Malaysian context and
beyond.
  All models released at
https://huggingface.co/collections/mesolitica/multimodal-malaysian-llm-65c6f893e03f78fa9e5c8859