地址链接：https://www.flyai.com/m/resnest50-528c19ca.pth
查看来源：https://github.com/zhanghang1989/ResNeSt
确定自己使用的框架并导入对应的库。导入库实现样例代码可参考 文档中心-预训练模型使用教程
在代码中实现加载预训练模型地址
from flyai.utils import remote_helper
path = remote_helper.get_remote_data('https://www.flyai.com/m/resnest50-528c19ca.pth')
from resnest.torch import resnest50
model = resnest50(pretrained=False)
state = torch.load(path)
model.load_state_dict(state, strict=True)
feature = model.fc.in_features
# num_classes 为类别数
model.fc = nn.Linear(in_features=feature, out_features=num_classes, bias=True)
resnest200_d2-ca88e41f.pth
查看来源：https://download.openmmlab.com/pretrain/third_party/resnest200_d2-ca88e41f.pthresnest269-51ae5f19.pth
查看来源：https://s3.us-west-1.wasabisys.com/encoding/models/resnest269-51ae5f19.zipresnest200-d7fd712f.pth
查看来源：https://s3.us-west-1.wasabisys.com/encoding/models/resnest200-d7fd712f.zipresnest101-966fb78c.pth
查看来源：https://s3.us-west-1.wasabisys.com/encoding/models/resnest101-966fb78c.zip