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# speech recognition
- Soltau, Hagen, Hank Liao, and Hasim Sak. "Neural Speech Recognizer: Acoustic-to-Word LSTM Model for Large Vocabulary Speech Recognition." arXiv preprint arXiv:1610.09975 (201…
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Good understanding of deep learning architectures like Multi-Layer Perceptron, Recurrent Neural Networks (RNNs), Long Short Term Memory models (LSTMs), Gated Recurrent Units (GRUs), and Convolutional …
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I'm really interested in your great work. Just curious, If it is possible that combine BART with loss truncation? Cuz the vanilla LSTM with attention is kind of out-of-date.
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Hi,
I recently trained an LSTM-with-attention based model using the following hparams:
python3.6 -m nmt.nmt \
--attention=luong \
--src=r --tgt=p \
--vocab_prefix=/home/hisham/nmt…
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@slundberg I have a question. To test Attention Mechanism, I fix the tenth column of input X equal y. This is my code:
```
def get_lstm_data(n, time_steps, input_dim, attention_col=10):
x = np…
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Hi, I am new to the attention mechanism and I found your codes, tutorials very helpful to beginners like me!
Currently, I am trying to use your attention decoder to do the sentiment analysis of the…
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Hi,
It seems from the source code that XLM Roberta is finetuned with the gradient updates based on the LSTM attention model. However, when I follow the README instructions and train the model on hi…
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This is the feature request for saving off the embeddings of the metamodels. Here is a list of all the deep learning metamodels:
- dna_regression
- lstm
- daglstm_regression
- hidden_daglstm_reg…
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Hi,
The optimization didn't work. So I just added the line :
"metrics_callback.on_validation_end( trainer)" after line 209 .
I also modified the class :
class MetricsCallback(Callback…
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As mentioned in the paper, the attention is to be applied on the hidden states of the LSTM, but in the code, it is done on the outputs instead of hidden states. Why is it like that ?