| model | supported by mindformers |
|---|---|
| llama2 | llama2_7b, llama2_13b, llama2_7b_lora, llama2_13b_lora, llama2_70b |
| llama3 | llama3_8b |
| glm2 | glm2_6b, glm2_6b_lora |
| glm3 | glm3_6b, glm3_6b_lora |
| gpt2 | gpt2, gpt2_13b |
| baichuan2 | baichuan2_7b, baichuan2_13b, baichuan2_7b_lora, baichuan2_13b_lora |
| qwen | qwen_7b, qwen_14b, qwen_7b_lora, qwen_14b_lora |
| qwen1.5 | qwen1.5-14b, qwen1.5-72b |
| codegeex2 | codegeex2_6b |
| codellama | codellama_34b |
| deepseek | deepseek-coder-33b-instruct |
| internlm | internlm_7b, internlm_20b, internlm_7b_lora |
| mixtral | mixtral-8x7b |
| wizardcoder | wizardcoder_15b |
| yi | yi_6b,yi_34b |
| model | supported by mindone |
|---|---|
| stable diffusion | sd 1.5/2.0, vanilla fine tune, lora, dreambooth |
| stable diffusion xl | sai style(stability AI) vanilla fine tune, lora, dreambooth |
| dit | text to image fine tune |
| latte | uncondition text to image fine tune |
| hpcai open sora | v1.0/1.1/1.2 large scale training with dp/sp/zero |
| pku open sora plan | v1.0/v1.1 large scale training with dp/sp/zero |
| animatediff | motion module and lora training |
| model | acc@1 | supported by mindcv |
|---|---|---|
| vgg11 | 71.86 | config |
| vgg13 | 72.87 | config |
| vgg16 | 74.61 | config |
| vgg19 | 75.21 | config |
| resnet18 | 70.21 | config |
| resnet34 | 74.15 | config |
| resnet50 | 76.69 | config |
| resnet101 | 78.24 | config |
| resnet152 | 78.72 | config |
| resnetv2_50 | 76.90 | config |
| resnetv2_101 | 78.48 | config |
| dpn92 | 79.46 | config |
| dpn98 | 79.94 | config |
| dpn107 | 80.05 | config |
| dpn131 | 80.07 | config |
| densenet121 | 75.64 | config |
| densenet161 | 79.09 | config |
| densenet169 | 77.26 | config |
| densenet201 | 78.14 | config |
| seresnet18 | 71.81 | config |
| seresnet34 | 75.36 | config |
| seresnet50 | 78.31 | config |
| seresnext26 | 77.18 | config |
| seresnext50 | 78.71 | config |
| skresnet18 | 73.09 | config |
| skresnet34 | 76.71 | config |
| skresnet50_32x4d | 79.08 | config |
| resnext50_32x4d | 78.53 | config |
| resnext101_32x4d | 79.83 | config |
| resnext101_64x4d | 80.30 | config |
| resnext152_64x4d | 80.52 | config |
| rexnet_x09 | 77.07 | config |
| rexnet_x10 | 77.38 | config |
| rexnet_x13 | 79.06 | config |
| rexnet_x15 | 79.94 | config |
| rexnet_x20 | 80.64 | config |
| resnest50 | 80.81 | config |
| resnest101 | 82.50 | config |
| res2net50 | 79.35 | config |
| res2net101 | 79.56 | config |
| res2net50_v1b | 80.32 | config |
| res2net101_v1b | 95.41 | config |
| googlenet | 72.68 | config |
| inceptionv3 | 79.11 | config |
| inceptionv4 | 80.88 | config |
| mobilenet_v1_025 | 53.87 | config |
| mobilenet_v1_050 | 65.94 | config |
| mobilenet_v1_075 | 70.44 | config |
| mobilenet_v1_100 | 72.95 | config |
| mobilenet_v2_075 | 69.98 | config |
| mobilenet_v2_100 | 72.27 | config |
| mobilenet_v2_140 | 75.56 | config |
| mobilenet_v3_small | 68.10 | config |
| mobilenet_v3_large | 75.23 | config |
| shufflenet_v1_g3_x0_5 | 57.05 | config |
| shufflenet_v1_g3_x1_5 | 67.77 | config |
| shufflenet_v2_x0_5 | 57.05 | config |
| shufflenet_v2_x1_0 | 67.77 | config |
| shufflenet_v2_x1_5 | 57.05 | config |
| shufflenet_v2_x2_0 | 67.77 | config |
| xception | 79.01 | config |
| ghostnet_50 | 66.03 | config |
| ghostnet_100 | 73.78 | config |
| ghostnet_130 | 75.50 | config |
| nasnet_a_4x1056 | 73.65 | config |
| mnasnet_0.5 | 68.07 | config |
| mnasnet_0.75 | 71.81 | config |
| mnasnet_1.0 | 74.28 | config |
| mnasnet_1.4 | 76.01 | config |
| efficientnet_b0 | 76.89 | config |
| efficientnet_b1 | 78.95 | config |
| regnet_x_200mf | 68.74 | config |
| regnet_x_400mf | 73.16 | config |
| regnet_x_600mf | 73.34 | config |
| regnet_x_800mf | 76.04 | config |
| regnet_y_200mf | 70.30 | config |
| regnet_y_400mf | 73.91 | config |
| regnet_y_600mf | 75.69 | config |
| regnet_y_800mf | 76.52 | config |
| mixnet_s | 75.52 | config |
| mixnet_m | 76.64 | config |
| mixnet_l | 78.73 | config |
| hrnet_w32 | 80.64 | config |
| hrnet_w48 | 81.19 | config |
| bit_resnet50 | 76.81 | config |
| bit_resnet50x3 | 80.63 | config |
| bit_resnet101 | 77.93 | config |
| repvgg_a0 | 72.19 | config |
| repvgg_a1 | 74.19 | config |
| repvgg_a2 | 76.63 | config |
| repvgg_b0 | 74.99 | config |
| repvgg_b1 | 78.81 | config |
| repvgg_b2 | 79.29 | config |
| repvgg_b3 | 80.46 | config |
| repvgg_b1g2 | 78.03 | config |
| repvgg_b1g4 | 77.64 | config |
| repvgg_b2g4 | 78.80 | config |
| repmlp_t224 | 76.71 | config |
| convnext_tiny | 81.91 | config |
| convnext_small | 83.40 | config |
| convnext_base | 83.32 | config |
| vit_b_32_224 | 75.86 | config |
| vit_l_16_224 | 76.34 | config |
| vit_l_32_224 | 73.71 | config |
| swintransformer_tiny | 80.82 | config |
| pvt_tiny | 74.81 | config |
| pvt_small | 79.66 | config |
| pvt_medium | 81.82 | config |
| pvt_large | 81.75 | config |
| pvt_v2_b0 | 71.50 | config |
| pvt_v2_b1 | 78.91 | config |
| pvt_v2_b2 | 81.99 | config |
| pvt_v2_b3 | 82.84 | config |
| pvt_v2_b4 | 83.14 | config |
| pit_ti | 72.96 | config |
| pit_xs | 78.41 | config |
| pit_s | 80.56 | config |
| pit_b | 81.87 | config |
| coat_lite_tiny | 77.35 | config |
| coat_lite_mini | 78.51 | config |
| coat_tiny | 79.67 | config |
| convit_tiny | 73.66 | config |
| convit_tiny_plus | 77.00 | config |
| convit_small | 81.63 | config |
| convit_small_plus | 81.80 | config |
| convit_base | 82.10 | config |
| convit_base_plus | 81.96 | config |
| crossvit_9 | 73.56 | config |
| crossvit_15 | 81.08 | config |
| crossvit_18 | 81.93 | config |
| mobilevit_xx_small | 68.90 | config |
| mobilevit_x_small | 74.98 | config |
| mobilevit_small | 78.48 | config |
| visformer_tiny | 78.28 | config |
| visformer_tiny_v2 | 78.82 | config |
| visformer_small | 81.76 | config |
| visformer_small_v2 | 82.17 | config |
| edgenext_xx_small | 71.02 | config |
| edgenext_x_small | 75.14 | config |
| edgenext_small | 79.15 | config |
| edgenext_base | 82.24 | config |
| poolformer_s12 | 77.33 | config |
| xcit_tiny_12_p16 | 77.67 | config |
| model | dataset | fscore | supported by mindocr |
|---|---|---|---|
| dbnet_mobilenetv3 | icdar2015 | 77.23 | config |
| dbnet_resnet18 | icdar2015 | 81.73 | config |
| dbnet_resnet50 | icdar2015 | 85.05 | config |
| dbnet++_resnet50 | icdar2015 | 86.74 | config |
| psenet_resnet152 | icdar2015 | 82.06 | config |
| east_resnet50 | icdar2015 | 84.87 | config |
| fcenet_resnet50 | icdar2015 | 84.12 | config |
| model | dataset | acc | supported by mindocr |
|---|---|---|---|
| svtr_tiny | IC03,13,15,IIIT,etc | 89.02 | config |
| crnn_vgg7 | IC03,13,15,IIIT,etc | 82.03 | config |
| crnn_resnet34_vd | IC03,13,15,IIIT,etc | 84.45 | config |
| rare_resnet34_vd | IC03,13,15,IIIT,etc | 85.19 | config |
| model | dataset | acc | supported by mindocr |
|---|---|---|---|
| mobilenetv3 | RCTW17,MTWI,LSVT | 94.59 | config |
| model | map | supported by mindyolo |
|---|---|---|
| yolov8_n | 37.2 | config |
| yolov8_s | 44.6 | config |
| yolov8_m | 50.5 | config |
| yolov8_l | 52.8 | config |
| yolov8_x | 53.7 | config |
| yolov7_t | 37.5 | config |
| yolov7_l | 50.8 | config |
| yolov7_x | 52.4 | config |
| yolov5_n | 27.3 | config |
| yolov5_s | 37.6 | config |
| yolov5_m | 44.9 | config |
| yolov5_l | 48.5 | config |
| yolov5_x | 50.5 | config |
| yolov4_csp | 45.4 | config |
| yolov4_csp(silu) | 45.8 | config |
| yolov3_darknet53 | 45.5 | config |
| yolox_n | 24.1 | config |
| yolox_t | 33.3 | config |
| yolox_s | 40.7 | config |
| yolox_m | 46.7 | config |
| yolox_l | 49.2 | config |
| yolox_x | 51.6 | config |
| yolox_darknet53 | 47.7 | config |
| model | supported by minddet |
|---|---|
| ssd_vgg16 | coming soon |
| ssd_mobilenetv1 | coming soon |
| ssd_mobilenetv2 | coming soon |
| ssd_resnet50 | coming soon |
| fasterrcnn | coming soon |
| maskrcnn_mobilenetv1 | coming soon |
| maskrcnn_resnet50 | coming soon |
| ocrnet | link |
| deeplab v3 | coming soon |
| deeplab v3 plus | coming soon |
| unet | coming soon |
| unet3d | coming soon |
| centernet | coming soon |
| pointpillar | coming soon |
| bevformer | coming soon |
| bevdet | coming soon |
| bevfusion | coming soon |
| uniad | coming soon |
MindSpore仅提供下载和预处理公共数据集的脚本。我们不拥有这些数据集，也不对它们的质量负责或维护。请确保您具有在数据集许可下使用该数据集的权限。在这些数据集上训练的模型仅用于非商业研究和教学目的。
致数据集拥有者：如果您不希望将数据集包含在MindSpore中，或者希望以任何方式对其进行更新，我们将根据要求删除或更新所有公共内容。请通过GitHub或Gitee与我们联系。非常感谢您对这个社区的理解和贡献。