| language: | |
| - en | |
| tags: | |
| - deepspeed | |
| - visualchat | |
| - multi-image | |
| - causal | |
| - chat | |
| license: apache-2.0 | |
| datasets: | |
| - openai/clip-vit-large-patch14 | |
| --- | |
| # Llama-2-13b-deepspeed-visualchat | |
| 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 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. | |