DiT-MoE
Large-scale Parameter Diffusion Transformer Model
CommonProductProgrammingDeep LearningDiffusion Models
DiT-MoE is a diffusion transformer model implemented in PyTorch that can scale up to 16 billion parameters while competing with dense networks and demonstrating highly optimized inference capabilities. It represents cutting-edge technology in deep learning for handling large-scale datasets, carrying significant research and application value.
DiT-MoE Visit Over Time
Monthly Visits
474564576
Bounce Rate
36.20%
Page per Visit
6.1
Visit Duration
00:06:34
