代码如下: model = Model().double() # Model is defined in another class File "/path/file.py", line 47, in <module>
state_dict = torch.hub.load_state_dict_from_urlt=wjbujfo
我想用Universal Sentence Encoder on TensorFlow Hub嵌入来计算Word Mover's Distance。据我所知,有人写了一个Bert to token embeddings based on pytorch,但它没有推广到tf-hub上的其他模型。是否有其他方法可以将tf-hub上的预训练模型转换为spaCy格式或word2vec格式?