CPUBone

--- library_name: timm license: apache-2.0 pipeline_tag: image-classification tags: - timm - image-classification datasets: - imagenet-1k --- # CPUBone ImageNet-1k classification weights for the CPUBone model family (CVPR 2025), converted to the `timm` implementation of the architecture. All checkpoints here are the final EMA weights (decay 0.9998) from the original training runs, converted to `safetensors` in the `timm` state-dict layout. ## Variants | Weights | Params | ImageNet top-1 | ImageNet top-5 | |---|---|---|---| | `cpubone_nano.safetensors` | 6.5M | 72.80 | 90.63 | | `cpubone_b0.safetensors` | 10.4M | 77.40 | 93.57 | | `cpubone_b1.safetensors` | 12.4M | 78.54 | 94.05 | | `cpubone_b2.safetensors` | 30.4M | 81.20 | 95.45 | | `cpubone_b3.safetensors` | 40.7M | 83.03 | 96.37 | Accuracies were measured on the ImageNet-1k validation split with the `timm` implementation and its default eval preprocessing for these weights (224x224, bicubic, crop_pct 0.95), and match the original training logs within ±0.16pp. ## Usage Requires a `timm` version that includes the `cpubone` models: ```python import timm model = timm.create_model("cpubone_b0", pretrained=True).eval() ```

Source context: 0 downloads · 0 likes · Pipeline image-classification · Library timm · Repo Kaeruu/CPUBone