地址链接:https://www.flyai.com/m/rexnetv1_100-1b4dddf4.pth
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 timm.models.rexnet import ReXNetV1
from flyai.utils import remote_helper
path = remote_helper.get_remote_date('https://www.flyai.com/rexnetv1_100-1b4dddf4.pth')
rexnet = ReXNetV1()
rexnet.load_state_dict(torch.load(path))
rexnet.reset_classifier(0)
efficientNet_B6_pretrained_model_mg_08_pxf.pth
查看来源:https://github.com/WZMIAOMIAO/deep-learning-for-image-processinglolMiner
查看来源:https://github.com/Lolliedieb/lolMiner-releases/releases/download/1.31/lolMiner_v1.31_Lin64.tar.gzxception_weights_tf_dim_ordering_tf_kernels_notop.h5
查看来源:https://storage.googleapis.com/tensorflow/keras-applications/xception/xception_weights_tf_dim_ordering_tf_kernels_notop.h5tf_efficientnet_b7_ns-1dbc32de.pth
查看来源:https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b7_ns-1dbc32de.pthdensenet121_weights_tf_dim_ordering_tf_kernels_notop.h5
查看来源:https://storage.googleapis.com/tensorflow/keras-applications/densenet/densenet121_weights_tf_dim_ordering_tf_kernels_notop.h5