--- 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.