usage.py

# Create the model.
network = CharRNN(dataset.vocabulary_size, 
                  dataset.sequence_length,
                  dropout_rate=0.5,
                  batch_size=512,
                  rnn_size=256, 
                  amount_layers=3,
                  embedding_size=512,
                  learning_rate=0.001,
                  clip_norm=5.0)
                  
# Load previous progress (assuming there is some!)
network.load()

# Train on the dataset previously established.
network.train(dataset, epochs=10)

# Create some starting tokens for inference.
tokens = dataset.empty_start_tokens
tokens = np.random.choice(list(dataset.token_to_char.keys()), dataset.sequence_length)

# Print random inference.
print(network.inference(tokens.tolist(), 
                        dataset, 
                        inference_length=60, 
                        temperature=0.5))
# Printed results.
>> ♀️
>> I am a conversation and personality of the looking for politics and will strong.