python -m torch.distributed.launch --nproc_per_node=8 main.py \ --model convnext_base --eval true \ --resume https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_1k_224.pth \ --input_size 224 --drop_path 0.2 \ --data_path /path/to/imagenet-1k ...
Code release for ConvNeXt model. Contribute to facebookresearch/ConvNeXt development by creating an account on GitHub.
convnext-tiny-22k-224.pth模型文件Et**on 上传170.25MB 文件格式 pth convnext-tiny-22k-224.pth模型文件 点赞(0) 踩踩(0) 反馈 所需:1 积分 电信网络下载 客户、银行、ERP三方沟通文档.doc 2024-11-20 17:09:28 积分:1 AR and VR的几大开源平台.rar 2024-11-20 16:34:45 积分:1 ...
convnext-base-22k-1k-224.pth Fa**过错上传深度学习模型参数 ConvNext的预训练模型参数:convnext_base_22k_1k_224.pth (0)踩踩(0) 所需:1积分
整体来说,ConvNeXt-Tiny模型表示在下图,训练使用AdamW优化器。 总结: ConvNeXt是一个向transformer网络靠拢的cnn模型,从作者的实验看出,每一点精度的提升都是经过大量的实验。 模型以及训练代码 训练在5分类的花数据集上在ConvNeXt-Tiny模型上准确率为92.3,在ConvNeXt-Tiny模型上准确率为93.2(可以更高,这里只训练了...
"convnext_large_22k": "https://dl.fbaipublicfiles.com/convnext/convnext_large_22k_224.pth", "convnext_xlarge_22k": "https://dl.fbaipublicfiles.com/convnext/convnext_xlarge_22k_224.pth", } url = model_urls['convnext_tiny_1k'] ...
def convnext_tiny(num_classes: int): # https://dl.fbaipublicfiles.com/convnext/convnext_tiny_1k_224_ema.pth model = ConvNeXt(depths=[3, 3, 9, 3], dims=[96, 192, 384, 768], num_classes=num_classes) return model def convnext_small(num_classes: int): ...
python -m torch.distributed.launch --nproc_per_node=8 main.py \ --model convnext_base --eval true \ --resume https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_1k_224.pth \ --input_size 224 --drop_path 0.2 \ --data_path /path/to/imagenet-1k This should give * Acc@...
Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tinynet,tinyvit,uniformer,volo,vanillanet,...
Code release for ConvNeXt model. Contribute to facebookresearch/ConvNeXt development by creating an account on GitHub.