| Model | Context | Top-1 (%) | Top-5 (%) | Params(M) | Recipe | Download |
|---|---|---|---|---|---|---|
| bit_resnet50 | D910x8-G | 76.81 | 93.17 | 25.55 | yaml | weights |
| bit_resnet50x3 | D910x8-G | 80.63 | 95.12 | 217.31 | yaml | weights |
| bit_resnet101 | D910x8-G | 77.93 | 93.75 | 44.54 | yaml | weights |
| coat_lite_tiny | D910x8-G | 77.35 | 93.43 | 5.72 | yaml | weights |
| coat_lite_mini | D910x8-G | 78.51 | 93.84 | 11.01 | yaml | weights |
| convit_tiny | D910x8-G | 73.66 | 91.72 | 5.71 | yaml | weights |
| convit_tiny_plus | D910x8-G | 77.00 | 93.60 | 9.97 | yaml | weights |
| convit_small | D910x8-G | 81.63 | 95.59 | 27.78 | yaml | weights |
| convit_small_plus | D910x8-G | 81.80 | 95.42 | 48.98 | yaml | weights |
| convit_base | D910x8-G | 82.10 | 95.52 | 86.54 | yaml | weights |
| convit_base_plus | D910x8-G | 81.96 | 95.04 | 153.13 | yaml | weights |
| ConvNeXt_tiny | D910x64-G | 81.91 | 95.79 | 28.59 | yaml | weights |
| ConvNeXt_small | D910x64-G | 83.40 | 96.36 | 50.22 | yaml | weights |
| ConvNeXt_base | D910x64-G | 83.32 | 96.24 | 88.59 | yaml | weights |
| crossvit_15 | D910x8-G | 81.08 | 95.33 | 27.27 | yaml | weights |
| crossvit_18 | D910x8-G | 81.93 | 95.75 | 43.27 | yaml | weights |
| densenet_121 | D910x8-G | 75.64 | 92.84 | 8.06 | yaml | weights |
| densenet_161 | D910x8-G | 79.09 | 94.66 | 28.90 | yaml | weights |
| densenet_169 | D910x8-G | 77.26 | 93.71 | 14.31 | yaml | weights |
| densenet_201 | D910x8-G | 78.14 | 94.08 | 20.24 | yaml | weights |
| dpn92 | D910x8-G | 79.46 | 94.49 | 37.79 | yaml | weights |
| dpn98 | D910x8-G | 79.94 | 94.57 | 61.74 | yaml | weights |
| dpn107 | D910x8-G | 80.05 | 94.74 | 87.13 | yaml | weights |
| dpn131 | D910x8-G | 80.07 | 94.72 | 79.48 | yaml | weights |
| edgenext_xx_small | D910x8-G | 71.02 | 89.99 | 1.33 | yaml | weights |
| edgenext_x_small | D910x8-G | 75.14 | 92.50 | 2.34 | yaml | weights |
| edgenext_small | D910x8-G | 79.15 | 94.39 | 5.59 | yaml | weights |
| edgenext_base | D910x8-G | 82.24 | 95.94 | 18.51 | yaml | weights |
| efficientnet_b0 | D910x64-G | 76.95 | 93.16 | 5.33 | yaml | weights |
| GoogLeNet | D910x8-G | 72.68 | 90.89 | 6.99 | yaml | weights |
| hrnet_w32 | D910x8-G | 80.64 | 95.44 | 41.30 | yaml | weights |
| hrnet_w48 | D910x8-G | 81.19 | 95.69 | 77.57 | yaml | weights |
| Inception_v3 | D910x8-G | 79.11 | 94.40 | 27.20 | yaml | weights |
| Inception_v4 | D910x8-G | 80.88 | 95.34 | 42.74 | yaml | weights |
| MixNet_s | D910x8-G | 75.52 | 92.52 | 4.17 | yaml | weights |
| MixNet_m | D910x8-G | 76.64 | 93.05 | 5.06 | yaml | weights |
| MnasNet-B1-0_75 | D910x8-G | 71.81 | 90.53 | 3.20 | yaml | weights |
| MnasNet-B1-1_0 | D910x8-G | 74.28 | 91.70 | 4.42 | yaml | weights |
| MnasNet-B1-1_4 | D910x8-G | 76.01 | 92.83 | 7.16 | yaml | weights |
| MobileNet_v1_025 | D910x8-G | 53.87 | 77.66 | 0.47 | yaml | weights |
| MobileNet_v1_050 | D910x8-G | 65.94 | 86.51 | 1.34 | yaml | weights |
| MobileNet_v1_075 | D910x8-G | 70.44 | 89.49 | 2.60 | yaml | weights |
| MobileNet_v1_100 | D910x8-G | 72.95 | 91.01 | 4.25 | yaml | weights |
| MobileNet_v2_075 | D910x8-G | 69.76 | 89.28 | 2.66 | yaml | weights |
| MobileNet_v2_100 | D910x8-G | 72.02 | 90.92 | 3.54 | yaml | weights |
| MobileNet_v2_140 | D910x8-G | 74.97 | 92.32 | 6.15 | yaml | weights |
| MobileNetV3_small_100 | D910x8-G | 67.81 | 87.82 | 2.55 | yaml | weights |
| MobileNetV3_large_100 | D910x8-G | 75.14 | 92.33 | 5.51 | yaml | weights |
| nasnet_a_4x1056 | D910x8-G | 73.65 | 91.25 | 5.33 | yaml | weights |
| PiT_xs | D910x8-G | 78.41 | 94.06 | 10.61 | yaml | weights |
| poolformer_s12 | D910x8-G | 77.33 | 93.34 | 11.92 | yaml | weights |
| PVT_tiny | D910x8-G | 74.81 | 92.18 | 13.23 | yaml | weights |
| PVT_small | D910x8-G | 79.66 | 94.71 | 24.49 | yaml | weights |
| PVT_medium | D910x8-G | 81.82 | 95.81 | 44.21 | yaml | weights |
| PVT_large | D910x8-G | 81.75 | 95.70 | 61.36 | yaml | weights |
| PVTV2_b0 | D910x8-G | 71.50 | 90.60 | 3.67 | yaml | weights |
| PVTV2_b1 | D910x8-G | 78.91 | 94.49 | 14.01 | yaml | weights |
| PVTV2_b2 | D910x8-G | 81.99 | 95.74 | 25.35 | yaml | weights |
| regnet_x_800mf | D910x8-G | 76.04 | 92.97 | 7.26 | yaml | weights |
| repmlp_t224 | D910x8-G | 76.68 | 93.30 | 38.30 | yaml | weights |
| repvgg_a0 | D910x8-G | 72.19 | 90.75 | 9.13 | yaml | weights |
| repvgg_a1 | D910x8-G | 74.19 | 91.89 | 14.12 | yaml | weights |
| repvgg_a2 | D910x8-G | 76.63 | 93.42 | 28.25 | yaml | weights |
| repvgg_b0 | D910x8-G | 74.99 | 92.40 | 15.85 | yaml | weights |
| repvgg_b1 | D910x8-G | 78.81 | 94.37 | 57.48 | yaml | weights |
| repvgg_b2 | D910x64-G | 79.29 | 94.66 | 89.11 | yaml | weights |
| repvgg_b3 | D910x64-G | 80.46 | 95.34 | 123.19 | yaml | weights |
| Res2Net50 | D910x8-G | 79.35 | 94.64 | 25.76 | yaml | weights |
| Res2Net101 | D910x8-G | 79.56 | 94.70 | 45.33 | yaml | weights |
| Res2Net50-v1b | D910x8-G | 80.32 | 95.09 | 25.77 | yaml | weights |
| Res2Net101-v1b | D910x8-G | 81.26 | 95.41 | 45.35 | yaml | weights |
| ResNeSt50 | D910x8-G | 80.81 | 95.16 | 27.55 | yaml | weights |
| ResNet18 | D910x8-G | 70.31 | 89.62 | 11.70 | yaml | weights |
| ResNet34 | D910x8-G | 74.15 | 91.98 | 21.81 | yaml | weights |
| ResNet50 | D910x8-G | 76.69 | 93.50 | 25.61 | yaml | weights |
| ResNet101 | D910x8-G | 78.24 | 94.09 | 44.65 | yaml | weights |
| ResNet152 | D910x8-G | 78.72 | 94.45 | 60.34 | yaml | weights |
| ResNetv2_50 | D910x8-G | 76.90 | 93.37 | 25.60 | yaml | weights |
| ResNetv2_101 | D910x8-G | 78.48 | 94.23 | 44.55 | yaml | weights |
| ResNeXt50_32x4d | D910x8-G | 78.53 | 94.10 | 25.10 | yaml | weights |
| ResNeXt101_32x4d | D910x8-G | 79.83 | 94.80 | 44.32 | yaml | weights |
| ResNeXt101_64x4d | D910x8-G | 80.30 | 94.82 | 83.66 | yaml | weights |
| ResNeXt152_64x4d | D910x8-G | 80.52 | 95.00 | 115.27 | yaml | weights |
| rexnet_x09 | D910x8-G | 77.07 | 93.41 | 4.13 | yaml | weights |
| rexnet_x10 | D910x8-G | 77.38 | 93.60 | 4.84 | yaml | weights |
| rexnet_x13 | D910x8-G | 79.06 | 94.28 | 7.61 | yaml | weights |
| rexnet_x15 | D910x8-G | 79.94 | 94.74 | 9.79 | yaml | weights |
| rexnet_x20 | D910x8-G | 80.64 | 94.99 | 16.45 | yaml | weights |
| SEResNet18 | D910x8-G | 71.81 | 90.49 | 11.80 | yaml | weights |
| SEResNet34 | D910x8-G | 75.38 | 92.50 | 21.98 | yaml | weights |
| SEResNet50 | D910x8-G | 78.32 | 94.07 | 28.14 | yaml | weights |
| SEResNeXt26_32x4d | D910x8-G | 77.17 | 93.42 | 16.83 | yaml | weights |
| SEResNeXt50_32x4d | D910x8-G | 78.71 | 94.36 | 27.63 | yaml | weights |
| shufflenet_v1_g3_x0_5 | D910x8-G | 57.05 | 79.73 | 0.73 | yaml | weights |
| shufflenet_v1_g3_x1_0 | D910x8-G | 67.77 | 87.73 | 1.89 | yaml | weights |
| shufflenet_v1_g3_x1_5 | D910x8-G | 71.53 | 90.17 | 3.48 | yaml | weights |
| shufflenet_v1_g3_x2_0 | D910x8-G | 74.02 | 91.74 | 5.50 | yaml | weights |
| shufflenet_v2_x0_5 | D910x8-G | 60.68 | 82.44 | 1.37 | yaml | weights |
| shufflenet_v2_x1_0 | D910x8-G | 69.51 | 88.67 | 2.29 | yaml | weights |
| shufflenet_v2_x1_5 | D910x8-G | 72.59 | 90.79 | 3.53 | yaml | weights |
| shufflenet_v2_x2_0 | D910x8-G | 75.14 | 92.13 | 7.44 | yaml | weights |
| skresnet18 | D910x8-G | 73.09 | 91.20 | 11.97 | yaml | weights |
| skresnet34 | D910x8-G | 76.80 | 93.10 | 22.31 | yaml | weights |
| skresnet50_32x4d | D910x8-G | 79.08 | 94.60 | 37.31 | yaml | weights |
| squeezenet_1.0 | D910x8-G | 59.01 | 81.01 | 1.25 | yaml | weights |
| squeezenet_1.0 | GPUx8-G | 59.49 | 81.22 | 1.25 | yaml | weights |
| squeezenet_1.1 | D910x8-G | 58.44 | 80.84 | 1.24 | yaml | weights |
| squeezenet_1.1 | GPUx8-G | 58.99 | 80.99 | 1.24 | yaml | weights |
| swin_tiny | D910x8-G | 80.82 | 94.80 | 33.38 | yaml | weights |
| vgg11 | D910x8-G | 72.00 | 90.50 | 132.86 | yaml | weights |
| vgg13 | D910x8-G | 72.75 | 91.03 | 133.04 | yaml | weights |
| vgg16 | D910x8-G | 74.53 | 92.05 | 138.35 | yaml | weights |
| vgg19 | D910x8-G | 75.20 | 92.52 | 143.66 | yaml | weights |
| visformer_tiny | D910x8-G | 78.28 | 94.15 | 10.33 | yaml | weights |
| visformer_tiny_v2 | D910x8-G | 78.82 | 94.41 | 9.38 | yaml | weights |
| visformer_small | D910x8-G | 81.73 | 95.88 | 40.25 | yaml | weights |
| visformer_small_v2 | D910x8-G | 82.17 | 95.90 | 23.52 | yaml | weights |
| vit_b_32_224 | D910x8-G | 75.86 | 92.08 | 87.46 | yaml | weights |
| vit_l_16_224 | D910x8-G | 76.34 | 92.79 | 303.31 | yaml | weights |
| vit_l_32_224 | D910x8-G | 73.71 | 90.92 | 305.52 | yaml | weights |
| Xception | D910x8-G | 79.01 | 94.25 | 22.91 | yaml | weights |
| xcit_tiny_12_p16 | D910x8-G | 77.67 | 93.79 | 7.00 | yaml | weights |
- Context: Training context denoted as {device}x{pieces}-{MS mode}, where mindspore mode can be G - graph mode or F - pynative mode with ms function. For example, D910x8-G is for training on 8 pieces of Ascend 910 NPU using graph mode.
- Top-1 and Top-5: Accuracy reported on the validation set of ImageNet-1K.