笔记 / Research / CausalDiscovery / Papers / Llava论文: Visual Instruction Tuning Llava论文: Visual Instruction Tuning #Research Llava论文: Visual Instruction Tuning Architecture Use GPT4 to generate dataset with VQA.As GPT4 is a purely languange model,we take captions and bounding boxes as the input to GPT,and thus generate 3 types of Q-A pairs. They’re like Xq Xv<STOP> Assistant:XC<STOP>\textbf{X}_q \ \textbf{X}_v\text{<STOP> Assistant:} \textbf{X}_C \text{<STOP>}Xq Xv<STOP> Assistant:XC<STOP> 上一篇 NOTEARS: Nonlinear Structural Equations with Alternative Regularization and Sparsity 下一篇 PPO算法原理