# 官方模型库 [](https://gitee.com/mindspore/docs/blob/r2.1/docs/mindspore/source_zh_cn/note/official_models.md) ## 领域套件与扩展包 ### 计算机视觉 #### 图像分类（骨干类） 以下数据基于Ascend 910环境和ImageNet-1K数据集获得。 | model | acc@1 | mindcv recipe | vanilla mindspore | | :-: | :-: | :-: | :-: | | vgg11 | 71.86 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | | | vgg13 | 72.87 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | | | vgg16 | 74.61 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/VGG/vgg16) | | vgg19 | 75.21 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vgg) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/VGG/vgg19) | | resnet18 | 70.21 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ResNet) | | resnet34 | 74.15 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ResNet) | | resnet50 | 76.69 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ResNet) | | resnet101 | 78.24 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ResNet) | | resnet152 | 78.72 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ResNet) | | resnetv2_50 | 76.90 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | | | resnetv2_101 | 78.48 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnetv2) | | | dpn92 | 79.46 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | | | dpn98 | 79.94 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | | | dpn107 | 80.05 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | | | dpn131 | 80.07 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/dpn) | | | densenet121 | 75.64 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | | | densenet161 | 79.09 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | | | densenet169 | 77.26 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | | | densenet201 | 78.14 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/densenet) | | | seresnet18 | 71.81 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | | | seresnet34 | 75.36 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | | | seresnet50 | 78.31 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | | | seresnext26 | 77.18 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | | | seresnext50 | 78.71 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/senet) | | | skresnet18 | 73.09 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | | | skresnet34 | 76.71 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | | | skresnet50_32x4d | 79.08 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/sknet) | | | resnext50_32x4d | 78.53 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | | | resnext101_32x4d | 79.83 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | | | resnext101_64x4d | 80.30 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | | | resnext152_64x4d | 80.52 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnext) | | | rexnet_x09 | 77.07 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | | | rexnet_x10 | 77.38 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | | | rexnet_x13 | 79.06 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | | | rexnet_x15 | 79.94 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | | | rexnet_x20 | 80.64 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/rexnet) | | | resnest50 | 80.81 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | | | resnest101 | 82.50 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/resnest) | | | res2net50 | 79.35 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | | | res2net101 | 79.56 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | | | res2net50_v1b | 80.32 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | | | res2net101_v1b | 95.41 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/res2net) | | | googlenet | 72.68 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/googlenet) | | | inceptionv3 | 79.11 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inceptionv3) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Inception/inceptionv3) | | inceptionv4 | 80.88 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/inceptionv4) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Inception/inceptionv4) | | mobilenet_v1_025 | 53.87 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | | | mobilenet_v1_050 | 65.94 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | | | mobilenet_v1_075 | 70.44 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | | | mobilenet_v1_100 | 72.95 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv1) | | | mobilenet_v2_075 | 69.98 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | | | mobilenet_v2_100 | 72.27 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | | | mobilenet_v2_140 | 75.56 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv2) | | | mobilenet_v3_small | 68.10 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | | | mobilenet_v3_large | 75.23 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilenetv3) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/MobileNet/mobilenetv3) | | shufflenet_v1_g3_x0_5 | 57.05 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv1) | | | shufflenet_v1_g3_x1_5 | 67.77 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv1) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ShuffleNet/shufflenetv1) | | shufflenet_v2_x0_5 | 57.05 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | | | shufflenet_v2_x1_0 | 67.77 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/ShuffleNet/shufflenetv2) | | shufflenet_v2_x1_5 | 57.05 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | | | shufflenet_v2_x2_0 | 67.77 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/shufflenetv2) | | | xception | 79.01 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xception) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Inception/xception) | | ghostnet_50 | 66.03 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | | | ghostnet_100 | 73.78 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | | | ghostnet_130 | 75.50 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/ghostnet) | | | nasnet_a_4x1056 | 73.65 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/nasnet) | | | mnasnet_0.5 | 68.07 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | | | mnasnet_0.75 | 71.81 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | | | mnasnet_1.0 | 74.28 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | | | mnasnet_1.4 | 76.01 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mnasnet) | | | efficientnet_b0 | 76.89 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Efficientnet/efficientnet-b0) | efficientnet_b1 | 78.95 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/efficientnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Efficientnet/efficientnet-b1) | efficientnet_b2 | 79.80 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Efficientnet/efficientnet-b2) | | efficientnet_b3 | 80.50 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Efficientnet/efficientnet-b3) | | efficientnet_v2 | 83.77 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Efficientnet/efficientnetv2) | | regnet_x_200mf | 68.74 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_x_400mf | 73.16 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_x_600mf | 73.34 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_x_800mf | 76.04 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_y_200mf | 70.30 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_y_400mf | 73.91 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_y_600mf | 75.69 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | regnet_y_800mf | 76.52 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/regnet) | | | mixnet_s | 75.52 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | | | mixnet_m | 76.64 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | | | mixnet_l | 78.73 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mixnet) | | | hrnet_w32 | 80.64 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | | | hrnet_w48 | 81.19 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/hrnet) | | | bit_resnet50 | 76.81 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | | | bit_resnet50x3 | 80.63 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | | | bit_resnet101 | 77.93 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/bit) | | | repvgg_a0 | 72.19 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_a1 | 74.19 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_a2 | 76.63 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b0 | 74.99 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b1 | 78.81 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b2 | 79.29 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b3 | 80.46 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b1g2 | 78.03 |[config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b1g4 | 77.64 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repvgg_b2g4 | 78.80 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repvgg) | | | repmlp_t224 | 76.71 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/repmlp) | | | convnext_tiny | 81.91 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | | | convnext_small | 83.40 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | | | convnext_base | 83.32 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convnext) | | | vit_b_32_224 | 75.86 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/VIT) | | vit_l_16_224 | 76.34| [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | | | vit_l_32_224 | 73.71 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/vit) | | | swintransformer_tiny | 80.82 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/swintransformer) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/SwinTransformer) | | pvt_tiny | 74.81 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | | | pvt_small | 79.66 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | | | pvt_medium | 81.82 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | | | pvt_large | 81.75 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvt) | | | pvt_v2_b0 | 71.50 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | | | pvt_v2_b1 | 78.91 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | | | pvt_v2_b2 | 81.99 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | | | pvt_v2_b3 | 82.84 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | | | pvt_v2_b4 | 83.14 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pvtv2) | | | pit_ti | 72.96 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | | | pit_xs | 78.41 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | | | pit_s | 80.56 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | | | pit_b | 81.87 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/pit) | | | coat_lite_tiny | 77.35 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | | | coat_lite_mini | 78.51 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | | | coat_tiny | 79.67 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/coat) | | | convit_tiny | 73.66 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | | | convit_tiny_plus | 77.00 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | | | convit_small | 81.63 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | | | convit_small_plus | 81.80 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | | | convit_base | 82.10 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | | | convit_base_plus | 81.96 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/convit) | | | crossvit_9 | 73.56 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | | | crossvit_15 | 81.08 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | | | crossvit_18 | 81.93 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/crossvit) | | | mobilevit_xx_small | 68.90 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | | | mobilevit_x_small | 74.98 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | | | mobilevit_small | 78.48 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/mobilevit) | | | visformer_tiny | 78.28 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | | | visformer_tiny_v2 | 78.82 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | | | visformer_small | 81.76 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | | | visformer_small_v2 | 82.17 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/visformer) | | | edgenext_xx_small | 71.02 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | | | edgenext_x_small | 75.14 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | | | edgenext_small | 79.15 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | | | edgenext_base | 82.24 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/edgenext) | | | poolformer_s12 | 77.33 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/poolformer) | | | xcit_tiny_12_p16 | 77.67 | [config](https://github.com/mindspore-lab/mindcv/tree/main/configs/xcit) | | ### 目标检测 以下数据基于Ascend 910环境和COCO2017数据集获得。 #### yolo | model | map | mindyolo recipe | vanilla mindspore | |:-: | :-: | :-: | :-: | | yolov8_n | 37.2 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | | | yolov8_s | 44.6 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | | | yolov8_m | 50.5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | | | yolov8_l | 52.8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | | | yolov8_x | 53.7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov8) | | | yolov7_t | 37.5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | | | yolov7_l | 50.8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | | | yolov7_x | 52.4| [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov7) | | | yolov5_n | 27.3 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | | | yolov5_s | 37.6 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/YOLOv5) | | yolov5_m | 44.9 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | | | yolov5_l | 48.5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | | | yolov5_x | 50.5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov5) | | | yolov4_csp | 45.4 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov4) | | | yolov4_csp(silu) | 45.8 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov4) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/YOLOv4) | | yolov3_darknet53 | 45.5 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolov3) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/YOLOv3) | | yolox_n | 24.1 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | | yolox_t | 33.3 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | | yolox_s | 40.7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | | yolox_m | 46.7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | | yolox_l | 49.2 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | | yolox_x | 51.6 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | | yolox_darknet53 | 47.7 | [config](https://github.com/mindspore-lab/mindyolo/tree/master/configs/yolox) | | #### 经典 | model | map | mind_series recipe | vanilla mindspore | | :-: | :-: | :-: | :-: | | ssd_vgg16 | 23.2 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/SSD)| | ssd_mobilenetv1 | 22.0 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/SSD)| | ssd_mobilenetv2 | 29.1 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/SSD)| | ssd_resnet50 | 34.3 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/SSD)| | fasterrcnn | 58 | [link](https://github.com/mindspore-lab/models/tree/master/official/cv/RCNN) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/FasterRCNN) | | maskrcnn_mobilenetv1 | coming soon | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/MaskRCNN/maskrcnn_mobilenetv1) | | maskrcnn_resnet50 | coming soon | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/MaskRCNN/maskrcnn_resnet50) | ### 语义分割 | model | mind_series recipe | vanilla mindspore | | :-: | :-: | :-: | | ocrnet | [link](https://github.com/mindspore-lab/models/tree/master/official/cv/OCRNet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/OCRNet/) | | deeplab v3 | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/DeepLabv3) | | deeplab v3 plus | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/DeepLabV3P) | | unet | | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Unet) | ### OCR #### 文本检测 | model |dataset | fscore | mindocr recipe | vanilla mindspore | :-: | :-: | :-: | :-: | :-: | | dbnet_mobilenetv3 | icdar2015 | 77.23 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/DBNet/) | | dbnet_resnet18 | icdar2015 | 81.73 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/DBNet/) | | dbnet_resnet50 | icdar2015 | 85.05 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/DBNet/) | | dbnet++_resnet50 | icdar2015 | 86.74 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/dbnet) | | | psenet_resnet152 | icdar2015 | 82.06 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/psenet) | [link](https://gitee.com/mindspore/models/tree/r2.1/research/cv/psenet) | | east_resnet50 | icdar2015 | 84.87 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/east) | [link](https://gitee.com/mindspore/models/tree/r2.1/research/cv/east) | | fcenet_resnet50 | icdar2015 | 84.12 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/det/fcenet) | | #### 文本识别 | model | dataset | acc | mindocr recipe | vanilla mindspore | :-: | :-: | :-: | :-: | :-: | | svtr_tiny | IC03,13,15,IIIT,etc | 89.02 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/svtr) | | | crnn_vgg7 | IC03,13,15,IIIT,etc | 82.03 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/crnn) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/CRNN) | | crnn_resnet34_vd | IC03,13,15,IIIT,etc | 84.45 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/crnn) | | | rare_resnet34_vd | IC03,13,15,IIIT,etc | 85.19 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/rare) | [link](https://gitee.com/mindspore/models/tree/r2.1/research/cv/crnn_seq2seq_ocr) | #### 文本方向分类 | model | dataset | acc | mindocr recipe | :-: | :-: | :-: | :-: | | mobilenetv3 | RCTW17,MTWI,LSVT | 94.59 | [config](https://github.com/mindspore-lab/mindocr/tree/main/configs/cls/mobilenetv3) | ### 人脸 | model | dataset | acc | mindface recipe | vanilla mindspore | :-: | :-: | :-: | :-: | :-: | | arcface_mobilefacenet-0.45g | MS1MV2 | 98.70 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | | | arcface_r50 | MS1MV2 | 99.76 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | | | arcface_r100 | MS1MV2 | 99.38 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/Arcface) | | arcface_vit_t | MS1MV2 | 99.71 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | | | arcface_vit_s | MS1MV2 | 99.76 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | | | arcface_vit_b | MS1MV2 | 99.81 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | | | arcface_vit_l | MS1MV2 | 99.75 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/recognition) | | | retinaface_mobilenet_0.25 | WiderFace | 90.77/88.2/74.76 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/detection) | [link](https://gitee.com/mindspore/models/tree/r2.1/research/cv/retinaface) | | retinaface_r50 | WiderFace | 95.07/93.61/84.84 | [config](https://github.com/mindspore-lab/mindface/tree/main/mindface/detection) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/cv/RetinaFace_ResNet50) | ### 语言模型 | model | mindformer recipe | vanilla mindspore | :-: | :-: | :-: | | bert_base | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/t5.md) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/nlp/Bert) | | t5_small | [config](https://github.com/mindspore-lab/mindformers/blob/master/docs/model_cards/bert.md) | | | gpt2_small | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/gpt2.md) | | gpt2_13b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/gpt2.md) | | gpt2_52b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/gpt2.md) | | pangu_alpha | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/pangualpha.md) | | glm_6b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/glm.md) | | glm_6b_lora | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/glm.md) | | llama_7b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/llama.md) | | llama_13b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/llama.md) | | llama_65b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/llama.md) | | llama_7b_lora | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/llama.md) | | bloom_560m | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/bloom.md) | | bloom_7.1b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/bloom.md) | | bloom_65b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/bloom.md) | | bloom_176b | [config](https://gitee.com/mindspore/mindformers/blob/dev/docs/model_cards/bloom.md) | ### 强化学习 | Algorithm | Discrete Action Space | Continuous Action Space | CPU | GPU | Ascend | Environment | Reward | | --- | --- | --- | --- | --- | --- | --- | --- | | [DQN](https://github.com/mindspore-lab/mindrl/tree/master/example/dqn) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [PPO](https://github.com/mindspore-lab/mindrl/tree/master/example/ppo) | / | ✅ | ✅ | ✅ | ✅ | [HalfCheetah-v2](https://www.gymlibrary.dev/environments/mujoco/half_cheetah/) | 4800 | | [AC](https://github.com/mindspore-lab/mindrl/tree/master/example/ac) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [A2C](https://github.com/mindspore-lab/mindrl/tree/master/example/a2c) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [DDPG](https://github.com/mindspore-lab/mindrl/tree/master/example/ddpg) | / | ✅ | ✅ | ✅ | ✅ | [HalfCheetah-v2](https://www.gymlibrary.dev/environments/mujoco/half_cheetah/) | 4800 | | [QMIX](https://github.com/mindspore-lab/mindrl/tree/master/example/qmix) | ✅ | / | ✅ | ✅ | ✅ | [SMAC/Simple Spread](https://github.com/oxwhirl/smac/) | 90%/-145 | | [SAC](https://github.com/mindspore-lab/mindrl/tree/master/example/sac) | / | ✅ | ✅ | ✅ | ✅ | [HalfCheetah-v2](https://www.gymlibrary.dev/environments/mujoco/half_cheetah/) | 4800 | | [TD3](https://github.com/mindspore-lab/mindrl/tree/master/example/td3) | / | ✅ | ✅ | ✅ | ✅ | [HalfCheetah-v2](https://www.gymlibrary.dev/environments/mujoco/half_cheetah/) | 4800 | | [C51](https://github.com/mindspore-lab/mindrl/tree/master/example/c51) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [A3C](https://github.com/mindspore-lab/mindrl/tree/master/example/a3c) | ✅ | / | / | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [CQL](https://github.com/mindspore-lab/mindrl/tree/master/example/cql) | / | ✅ | ✅ | ✅ | ✅ | [Hopper-v0](https://www.gymlibrary.dev/environments/mujoco/hopper) | 3500 | | [MAPPO](https://github.com/mindspore-lab/mindrl/tree/master/example/mappo) | ✅ | / | ✅ | ✅ | ✅ | [Simple Spread](https://github.com/openai/multiagent-particle-envs) | -145 | | [GAIL](https://github.com/mindspore-lab/mindrl/tree/master/example/gail) | / | ✅ | ✅ | ✅ | ✅ | [HalfCheetah-v2](https://www.gymlibrary.dev/environments/mujoco/half_cheetah/) | 4800 | | [AWAC](https://github.com/mindspore-lab/mindrl/tree/master/example/awac) | / | ✅ | ✅ | ✅ | ✅ | [Ant-v2](https://www.gymlibrary.dev/environments/mujoco/ant) | 5000 | | [Dreamer](https://github.com/mindspore-lab/mindrl/tree/master/example/dreamer) | / | ✅ | / | ✅ | ✅ | [Walker-walk](https://github.com/deepmind/dm_control) | 900 | | [IQL](https://github.com/mindspore-lab/mindrl/tree/master/example/iql) | / | ✅ | ✅ | ✅ | ✅ | [Walker2d-v2](https://www.gymlibrary.dev/environments/mujoco/walker2d/) | 3000 | | [MADDPG](https://github.com/mindspore-lab/mindrl/tree/master/example/maddpg) | ✅ | / | ✅ | ✅ | ✅ | [simple_spread](https://pettingzoo.farama.org/environments/mpe/simple_spread/) | -140 | | [Double DQN](https://github.com/mindspore-lab/mindrl/tree/master/example/double_dqn) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [Policy Gradient](https://github.com/mindspore-lab/mindrl/tree/master/example/pg) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | | [Dueling DQN](https://github.com/mindspore-lab/mindrl/tree/master/example/dueling_dqn) | ✅ | / | ✅ | ✅ | ✅ | [CartPole-v0](https://www.gymlibrary.dev/environments/classic_control/cart_pole/) | 195 | ## 科学计算套件 | 领域 | 网络 | MindSpore实现 | Ascend | GPU | |------|--------------------------------------------------------------------------------------------------------------------------------------------------|:------------------------------------------------------------------------------------------------------------------------------------------------:|:------:|:---:| | 通用物理 | [deepbsde](https://www.pnas.org/doi/10.1073/pnas.1718942115) | [Link](https://gitee.com/mindspore/models/blob/r2.1/research/hpc/deepbsde/README.md#) | | ✅ | | 通用物理 | [pfnn](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308597) | [Link](https://gitee.com/mindspore/models/blob/r2.1/research/hpc/pfnn/README_CN.md#) | | ✅ | | 通用物理 | [pinns](https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125) | [Link](https://gitee.com/mindspore/models/blob/r2.1/research/hpc/pinns/README_CN.md#) | | ✅ | | 海洋物理 | [ocean_model](https://gmd.copernicus.org/articles/12/4729/2019/) | [Link](https://gitee.com/mindspore/models/blob/r2.1/research/hpc/ocean_model/README.md#) | | ✅ | | 电磁学 | [incremental_learning](https://arxiv.org/abs/2111.08823) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindElec/examples/physics_driven/incremental_learning/README_CN.md#) | ✅ | ✅ | | 电磁学 | [pinn_fwi](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JB023120) | | ✅ | ✅ | | 电磁学 | [time_domain_maxwell](https://www.ijcai.org/proceedings/2022/533) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindElec/examples/physics_driven/time_domain_maxwell/README_CN.md#) | ✅ | ✅ | | 电磁学 | [frequency_domain_maxwell](https://arxiv.org/abs/2107.06164) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindElec/examples/physics_driven/frequency_domain_maxwell/README_CN.md#) | ✅ | ✅ | | 电磁学 | [AD_FDTD](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindElec/examples/AD_FDTD/README_CN.md#) | ✅ | ✅ | | 电磁学 | [SED_ANN](https://gitee.com/mindspore/mindscience/tree/r0.3/MindElec/examples/data_driven/sed_ann) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindElec/examples/data_driven/sed_ann/README_CN.md#) | ✅ | ✅ | | 电磁学 | [Metasurface_holograms](https://www.researching.cn/articles/OJ44d3746c3db8c1e1) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindElec/examples/metasurface/metasurface_holograms/README_CN.md#) | ✅ | ✅ | | 计算生物 | [MEGA-Fold](https://arxiv.org/abs/2206.12240v1) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/MEGAProtein/README_CN.md#) | ✅ | ✅ | | 计算生物 | [MEGA-EvoGen](https://arxiv.org/abs/2208.09652) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/MEGAProtein/README_CN.md#) | ✅ | ✅ | | 计算生物 | [MEGA-Assessment](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/MEGAProtein/README_CN.md#) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/MEGAProtein/README_CN.md#) | ✅ | ✅ | | 计算生物 | [ColabDesign](https://www.biorxiv.org/content/10.1101/2021.11.10.468128.abstract) | [Link](https://gitee.com/mindspore/mindscience/tree/r0.3/MindSPONGE/applications/research/Colabdesign) | ✅ | ✅ | | 计算生物 | [DeepDR](https://academic.oup.com/bioinformatics/article/35/24/5191/5497253) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/DeepDR/README.md#) | ✅ | ✅ | | 计算生物 | [DeepFRI](https://www.nature.com/articles/s41467-021-23303-9) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/DeepFRI/README_CN.md#) | ✅ | ✅ | | 计算生物 | [FAAST](https://www.biorxiv.org/content/10.1101/2023.04.14.536890v1) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/FAAST/README_CN.md#) | ✅ | ✅ | | 计算生物 | [JT-VAE](https://www.biorxiv.org/content/10.1101/2023.04.14.536890v1) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/JT-VAE/README.md#) | ✅ | ✅ | | 计算生物 | [KGNN](https://www.ijcai.org/Proceedings/2020/0380.pdf) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/KGNN/README.md#) | ✅ | ✅ | | 计算生物 | [MG-BERT](https://academic.oup.com/bib/article-abstract/22/6/bbab152/6265201) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/MG_BERT/README.md#) | ✅ | ✅ | | 计算生物 | [Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/Multimer/README.md#) | ✅ | ✅ | | 计算生物 | [ProteinMPNN](https://www.science.org/doi/abs/10.1126/science.add2187) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/ProteinMPNN/README.md#) | ✅ | ✅ | | 计算生物 | [UFold](https://doi.org/10.1093/nar/gkab1074) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/UFold/README_CN.md#) | ✅ | ✅ | | 计算生物 | [ESM-IF1](https://proceedings.mlr.press/v162/hsu22a.html) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/esm/README_CN.md#) | ✅ | ✅ | | 计算生物 | [ESM2](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1.full.pdf) | [Link](https://gitee.com/mindspore/mindscience/tree/r0.3/MindSPONGE/mindsponge/python/pipeline/models/esm2) | ✅ | ✅ | | 计算生物 | [Grover](https://proceedings.neurips.cc/paper/2020/file/94aef38441efa3380a3bed3faf1f9d5d-Paper.pdf) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/grover/README.md#) | ✅ | ✅ | | 计算生物 | [Pafnucy](https://doi.org/10.1093/bioinformatics/bty374) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindSPONGE/applications/research/pafnucy/README.md#) | ✅ | ✅ | | 计算生物 | [SchNet](https://arxiv.org/abs/1706.08566) | [Link](https://gitee.com/mindspore/mindscience/tree/r0.3/MindSPONGE/cybertron) | ✅ | ✅ | | 计算生物 | [MolCT](https://arxiv.org/abs/2012.11816) | [Link](https://gitee.com/mindspore/mindscience/tree/r0.3/MindSPONGE/cybertron) | ✅ | ✅ | | 计算生物 | [PhysNet](https://arxiv.org/abs/1902.08408) | [Link](https://gitee.com/mindspore/mindscience/tree/r0.3/MindSPONGE/cybertron) | ✅ | ✅ | | 计算流体 | [FNO1D](https://arxiv.org/abs/2010.08895) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/burgers_fno/FNO1D_CN.ipynb) | ✅ | ✅ | | 计算流体 | [KNO1D](https://arxiv.org/abs/2301.10022) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/burgers_kno/README_CN.md#) | ✅ | ✅ | | 计算流体 | [FNO2D](https://arxiv.org/abs/2010.08895) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/navier_stokes_fno/FNO2D_CN.ipynb) | ✅ | ✅ | | 计算流体 | [KNO2D](https://arxiv.org/abs/2301.10022) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/navier_stokes_kno/README_CN.md#) | ✅ | ✅ | | 计算流体 | [FNO3D](https://arxiv.org/abs/2010.08895) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/navier_stokes_3d_fno/FNO3D_CN.ipynb) | ✅ | ✅ | | 计算流体 | [CAE-LSTM](https://doi.org/10.13700/j.bh.1001-5965.2022.0085) | | ✅ | ✅ | | 计算流体 | [eHDNN](https://doi.org/10.1016/j.ast.2022.107636) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/transonic_buffet_ehdnn/README_CN.md#) | ✅ | ✅ | | 计算流体 | [HDNN](https://doi.org/10.1016/j.ast.2022.107636) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/move_boundary_hdnn/README_CN.md#) | ✅ | ✅ | | 计算流体 | [ViT](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/airfoil/2D_steady/2D_steady_CN.ipynb) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_driven/airfoil/2D_steady/README_CN.md#) | ✅ | ✅ | | 计算流体 | [PeRCNN](https://www.nature.com/articles/s42256-023-00685-7) | | ✅ | ✅ | | 计算流体 | [Burgers1D](https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/physics_driven/burgers/README_CN.md#) | ✅ | ✅ | | 计算流体 | [Cylinder Flow](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/physics_driven/cylinder_flow/navier_stokes2D_CN.ipynb) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/physics_driven/cylinder_flow/README_CN.md#) | ✅ | ✅ | | 计算流体 | [PDE-Net](https://arxiv.org/abs/1710.09668) | [Link](https://gitee.com/mindspore/mindscience/blob/r0.3/MindFlow/applications/data_mechanism_fusion/variant_linear_coe_pde_net/README_CN.md#) | ✅ | ✅ | ## 大模型套件 ### Transformers | model | dataset | metric | score | mindformers config | |----------------------------------|-------------|--------------------------------------|-----------------------------|----------------------------------------------------------------------------------------------------------------------------------| | bert_base_uncased | wiki | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/bert/run_bert_base_uncased.yaml) | | bert_tiny_uncased | wiki | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/bert/run_bert_tiny_uncased.yaml) | | qa_bert_base_uncased | SQuAD v1.1 | EM / F1 | 80.74 / 88.33 | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/qa/run_qa_bert_base_uncased.yaml) | | tokcls_bert_base_chinese_cluener | CLUENER | Entity F1 | 0.7905 | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/tokcls/run_tokcls_bert_base_chinese_cluener.yaml) | | txtcls_bert_base_uncased_mnli | Mnli | Entity F1 | 84.80% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/txtcls/run_txtcls_bert_base_uncased_mnli.yaml) | | clip_vit_b_32 | Cifar100 | Accuracy | 57.24% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/clip/run_clip_vit_b_32_zero_shot_image_classification_cifar100.yaml) | | clip_vit_b_16 | Cifar100 | Accuracy | 61.41% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/clip/run_clip_vit_b_16_zero_shot_image_classification_cifar100.yaml) | | clip_vit_l_14 | Cifar100 | Accuracy | 69.67% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/clip/run_clip_vit_l_14_zero_shot_image_classification_cifar100.yaml) | | clip_vit_l_14@336 | Cifar100 | Accuracy | 68.19% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/clip/run_clip_vit_l_14@336_zero_shot_image_classification_cifar100.yaml) | | filip_vit_l_14 | - | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/filip/run_filip_vit_l_14.yaml) | | glm_6b | ADGEN | BLEU-4 / Rouge-1 / Rouge-2 / Rouge-l | 8.42 / 31.75 / 7.98 / 25.28 | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/glm/run_glm_6b_infer.yaml) | | gpt2 | wikitext-2 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/gpt2/run_gpt2.yaml) | | gpt2_13b | wikitext-2 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/gpt2/run_gpt2_13b.yaml) | | gpt2_52b | wikitext-2 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/gpt2/run_gpt2_52b.yaml) | | llama_7b | alpac | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/llama/run_llama_7b.yaml) | | llama_13b | alpac | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/llama/run_llama_13b.yaml) | | llama_65b | alpac | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/llama/run_llama_65b.yaml) | | mae_vit_base_p16 | ImageNet-1K | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/mae/run_mae_vit_base_p16_224_800ep.yaml) | | vit_base_p16 | ImageNet-1K | Accuracy | 83.71% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/vit/run_vit_base_p16_224_100ep.yaml) | | pangualpha_2_6b | 悟道数据集 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/pangualpha/run_pangualpha_2_6b.yaml) | | pangualpha_13b | 悟道数据集 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/pangualpha/run_pangualpha_13b.yaml) | | swin_base_p4w7 | ImageNet-1K | Accuracy | 83.44% | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/swin/run_swin_base_p4w7_224_100ep.yaml) | | t5_small | WMT16 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/t5/run_t5_small_on_wmt16.yaml) | | t5_tiny | WMT16 | - | - | [config](https://gitee.com/mindspore/mindformers/blob/dev/configs/t5/run_t5_tiny_on_wmt16.yaml) | ### 推荐 | model | dataset | auc | mindrec recipe | vanilla mindspore | | --- | --- | --- | --- | --- | | Wide&Deep | Criteo | 0.8 | [link](https://github.com/mindspore-lab/mindrec/tree/r0.3/models/wide_deep) | [link](https://gitee.com/mindspore/models/tree/r2.1/official/recommend/Wide_and_Deep) | | Deep&Cross Network (DCN) | Criteo | 0.8 | [link](https://github.com/mindspore-lab/mindrec/tree/r0.3/models/deep_and_cross) | [link](https://gitee.com/mindspore/models/tree/r2.1/research/recommend/deep_and_cross) |