convnext_xlargecvt_t=convnext_tiny()cvt_s=convnext_small()cvt_b=convnext_base()cvt_l=convnext_large()cvt_x=convnext_xlarge()W021121:12:49.976547686device_context.cc:447]PleaseNOTE:device:0,GPUComputeCapability:7.0,DriverAPIVersion:10.1,RuntimeAPIVersion:10.1W021121:12:49.982038686device_cont...
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
def convnext_base(pretrained=False, in_22k=False, **kwargs): model = ConvNeXt(depths=[3, 3, 27, 3], dims=[128, 256, 512, 1024], **kwargs) if pretrained: url = model_urls['convnext_base_22k'] if in_22k else model_urls['convnext_base_1k'] checkpoint = torch.hub.load_stat...
In [3] # 配置模型 from ConvNeXt import convnext_tiny, convnext_small, convnext_base, convnext_large, convnext_xlarge cvt_t = convnext_tiny() cvt_s = convnext_small() cvt_b = convnext_base() cvt_l = convnext_large() cvt_x = convnext_xlarge() W0211 21:12:49.976547 686 ...
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ConvNeXT (base-sized model) ConvNeXT model pre-trained on ImageNet-22k and fine-tuned on ImageNet-1k at resolution 384x384. It was introduced in the paper A ConvNet for the 2020s by Liu et al. and first released in this repository. Disclaimer: The team releasing ConvNeXT did not writ...
End-to-end IN-1K fine-tuning setting for Base (B), Large (L), and Huge (H) models End-to-end IN-22K intermediate fine-tuning settings End-to-end IN-1K fine-tuning settings (after IN-22K intermediate fine-tuning) 协同设计 可以发现,在不修改模型架构的情况下使用 FCMAE 框架对表示学习质...
End-to-end IN-1K fine-tuning setting for Base (B), Large (L), and Huge (H) models End-to-end IN-22K intermediate fine-tuning settings End-to-end IN-1K fine-tuning settings (after IN-22K intermediate fine-tuning) 协同设计 可以发现,在不修改模型架构的情况下使用 FCMAE 框架对表示学习质...
今年(2022)一月份,Facebook AI Research和UC Berkeley一起发表了一篇文章A ConvNet for the 2020s,在文章中提出了ConvNeXt纯卷积神经网络,它对标的是2021年非常火的Swin Transformer,通过一系列实验比对,在相同的FLOPs下,ConvNeXt相比Swin Transformer拥有更快的推理速度以及更高的准确率,在ImageNet 22K上ConvNeXt-XL...
def convnext_base(num_classes: int): # https://dl.fbaipublicfiles.com/convnext/convnext_base_1k_224_ema.pth # https://dl.fbaipublicfiles.com/convnext/convnext_base_22k_224.pth model = ConvNeXt(depths=[3, 3, 27, 3], dims=[...