MoshiVis

MoshiVis Overview

MoshiVis is a cutting-edge Vision Speech Model (VSM) designed to facilitate engaging discussions about images while maintaining a natural conversational style. Leveraging the foundational speech model Moshi, it introduces significant improvements with an additional 206M adapter parameters on top of the base model.

Key Features

• Multi-Backend Support: Operates with three distinct backends (PyTorch, Rust, MLX), providing flexibility for various environments.
• WebUI Frontend: Offers a user-friendly interface to interact with the model, enhancing the user experience with echo cancellation features.
• Real-time Interaction: Maintains low latency for dynamic conversations using a cross-attention mechanism that infuses visual information into the speech tokens stream.
• Extensive Model Variants: Releases numerous compatible variants of the model tailored to different use cases and backend capabilities.
• Open-source Commitment: All model weights are available under the CC-BY 4.0 license, promoting collaboration and transparency in AI development.

Benefits

• Facilitates natural and fluid dialogues about visual content, pushing the boundaries of AI interactions.
• Designed for researchers and developers, enabling them to run and contribute to a versatile platform.
• Ensures efficient memory usage and performance with shared projection weights and a gating mechanism.

Highlights

• Live demo available for immediate interaction with the MoshiVis model.
• Comprehensive documentation and support for troubleshooting various backend setups.
• Committed to community-driven development with opportunities for feedback and contribution.