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- Paper - [ BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding(2018)] ( https://arxiv.org/abs/1810.04805 )
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- Colab - [ BERT_Torch.ipynb] ( https://colab.research.google.com/github/graykode/nlp-tutorial/blob/master/5-2.BERT/BERT_Torch.ipynb )
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+ | Model | Example | Framework | Lines(torch/tensor) |
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+ | :------------------------: | :--------------------------------: | :-----------: | :-----------------: |
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+ | NNLM | Predict Next Word | Torch, Tensor | 67/83 |
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+ | Word2Vec(Softmax) | Embedding Words and Show Graph | Torch, Tensor | 77/94 |
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+ | TextCNN | Sentence Classification | Torch, Tensor | 94/99 |
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+ | TextRNN | Predict Next Step | Torch, Tensor | 70/88 |
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+ | TextLSTM | Autocomplete | Torch, Tensor | 73/78 |
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+ | Bi-LSTM | Predict Next Word in Long Sentence | Torch, Tensor | 73/78 |
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+ | Seq2Seq | Change Word | Torch, Tensor | 93/111 |
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+ | Seq2Seq with Attention | Translate | Torch, Tensor | 108/118 |
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+ | Bi-LSTM with Attention | Binary Sentiment Classification | Torch, Tensor | 92/104 |
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+ | Transformer | Translate | Torch | 222/0 |
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+ | Greedy Decoder Transformer | Translate | Torch | 246/0 |
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+ | BERT | how to train | Torch | 242/0 |
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