README.md

metadata

language:
  - en
tags:
  - deepspeed
  - visualchat
  - multi-image
  - causal
  - chat
license: apache-2.0
datasets:
  - openai/clip-vit-large-patch14

---

Llama-2-13b-deepspeed-visualchat

ATTENTION: this encoder needs QwenCLIP model

DeepSpeed-VisualChat is a scalable, efficient, and user-friendly multi-modal training pipeline that leverages a novel multi-modal causal attention mechanism for better alignment of visual and text features. It uses data blending techniques to address the scarcity of interleaved text-and-image inputs in datasets.

The framework trains using a 2B visual encoder from QWen-VL and a 13B-70B language decoder from LLaMA-2, showcasing its extraordinary scalability. DeepSpeed-VisualChat is now open-sourced and encourages community contributions and collaborations. Visit the GitHub page to get started.