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  • 1
    seq2seq-couplet

    seq2seq-couplet

    Play couplet with seq2seq model

    ...Its purpose is not general machine translation, but a specialized text generation task in which the model produces a matching second line for a given first line in the style of traditional couplets. The repository includes the code needed to train the model, configure file paths and hyperparameters, and evaluate progress through loss and BLEU score tracking. It also supports serving the trained model through a web service, allowing users to interact with the system after training is complete. In addition to local execution, the project includes Docker files, which make it easier to package and deploy the application in a more reproducible way. The repository also points users to an external dataset source and documents vocabulary formatting requirements for custom datasets, showing that it is meant for both experimentation and extension.
    Downloads: 0 This Week
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  • 2
    NLG-Eval

    NLG-Eval

    Evaluation code for various unsupervised automated metrics

    NLG-Eval is a toolkit for evaluating the quality of natural language generation (NLG) outputs using multiple automated metrics such as BLEU, METEOR, and ROUGE.
    Downloads: 1 This Week
    Last Update:
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  • 3
    SRU

    SRU

    Training RNNs as Fast as CNNs

    ...SRU achieves 5--9x speed-up over cuDNN-optimized LSTM on classification and question answering datasets, and delivers stronger results than LSTM and convolutional models. We also obtain an average of 0.7 BLEU improvement over the Transformer model on the translation by incorporating SRU into the architecture. The experimental code and SRU++ implementation are available on the dev branch which will be merged into master later.
    Downloads: 0 This Week
    Last Update:
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