地址链接:https://www.flyai.com/m/resnest269-51ae5f19.pth
查看来源:https://s3.us-west-1.wasabisys.com/encoding/models/resnest269-51ae5f19.zip
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
# ImageNet预训练模型# 使用参考 https://hangzhang.org/PyTorch-Encoding/model_zoo/imagenet.html# 下载路径参考 https://github.com/zhanghang1989/PyTorch-Encoding/blob/master/encoding/models/model_store.py# 必须使用该方法下载模型,然后加载from flyai.utils import remote_helperpath = remote_helper.get_remote_date('https://www.flyai.com/m/resnest269-51ae5f19.pth')# 命令行运行 git clone https://github.com/zhanghang1989/PyTorch-Encodingmodel = encoding.models.get_model('ResNeSt269', pretrained=False)model.load_state_dict(torch.load(path))
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