Hierarchical-attention-networks-pytorch and tf-han
These two tools are competitors, as both implement the Hierarchical Attention Networks model for document classification, but tool A uses PyTorch while tool B uses TensorFlow.
About Hierarchical-attention-networks-pytorch
vietnh1009/Hierarchical-attention-networks-pytorch
Hierarchical Attention Networks for document classification
Implements two-level attention mechanisms at word and sentence levels to capture document structure, with GloVe word embeddings (50-300d) initialized in the embedding layer rather than default random initialization. Built on PyTorch with early stopping regularization and TensorBoard integration for training visualization. Includes a web demo interface and pre-trained models evaluated across eight datasets (AG News, DBPedia, Yelp, Amazon, Yahoo Answers) with configurable batch size, learning rate, and embedding dimensions.
About tf-han
shengc/tf-han
TensorFlow Implementation For [Hierarchical Attention Networks for Document Classification](http://www.cs.cmu.edu/~./hovy/papers/16HLT-hierarchical-attention-networks.pdf)
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