每个推荐都保留与其仓库、审计和安装路径的明确关联。
Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.
[ICLR2025] Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion
Official PyTorch Implementation of "Scalable Autoregressive Image Generation with Mamba"
每个推荐都保留与其仓库、审计和安装路径的明确关联。
Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.
[ICLR2025] Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion
Official PyTorch Implementation of "Scalable Autoregressive Image Generation with Mamba"
每个推荐都保留与其仓库、审计和安装路径的明确关联。
Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.
[ICLR2025] Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion
Official PyTorch Implementation of "Scalable Autoregressive Image Generation with Mamba"
每个推荐都保留与其仓库、审计和安装路径的明确关联。
Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images
A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.
[ICLR2025] Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State Fusion
Official PyTorch Implementation of "Scalable Autoregressive Image Generation with Mamba"