metadata
library_name: pytorch
EfficientViT is a new family of high-resolution vision models with novel multi-scale linear attention. As such, EfficientViT delivers remarkable performance gains over previous state-of-the-art models with significant speedup on diverse hardware platforms, including mobile CPU, edge GPU, and cloud GPU.
Original paper: EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction
EfficientViT-L2
EfficientViT is a new family of vision models for efficient high-resolution dense prediction. The core building block of EfficientViT is a new lightweight multi-scale linear attention module that achieves global receptive field and multi-scale learning with only hardware-efficient operations.
Model Configuration:
- Reference implementation: EfficientViT-L2
- Original Weight: l2.pt
- Dataset: ADE20K
- Resolution: 3x512x512
- Support Cooper version:
- Cooper SDK: [2.5.4]
- Cooper Foundry: [2.3]
| Model | Device | compression | Model Link |
|---|---|---|---|
| EfficientViT-L2 | N1-655 | Activation_fp16 | Model_Link |
| EfficientViT-L2 | CV7 | Activation_fp16 | Model_Link |
| EfficientViT-L2 | CV72 | Activation_fp16 | Model_Link |
| EfficientViT-L2 | CV75 | Activation_fp16 | Model_Link |