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Practical PyTorch: Generating Shakespeare with a Character-Level RNN


Download this Shakespeare dataset (from Andrej Karpathy's char-rnn) and save as shakespeare.txt

Jupyter Notebook

The Jupyter Notebook version of the tutorial describes the model and steps in detail.

Python scripts

Run train.py with a filename to train and save the network:

> python train.py shakespeare.txt

Training for 2000 epochs...
(10 minutes later)
Saved as shakespeare.pt

After training the model will be saved as [filename].pt — now run generate.py with that filename to generate some new text:

> python generate.py shakespeare.pt --prime_str "Where"

Where, you, and if to our with his drid's
Weasteria nobrand this by then.

It his zersit at he

Training options

Usage: train.py [filename] [options]

--n_epochs         Number of epochs to train
--print_every      Log learning rate at this interval
--hidden_size      Hidden size of GRU
--n_layers         Number of GRU layers
--learning_rate    Learning rate
--chunk_len        Length of chunks to train on at a time

Generation options

Usage: generate.py [filename] [options]

-p, --prime_str      String to prime generation with
-l, --predict_len    Length of prediction
-t, --temperature    Temperature (higher is more chaotic)