Load pretrained weights and predict with GPT-2.
pip install keras-gpt-2import os
from keras_gpt_2 import load_trained_model_from_checkpoint, get_bpe_from_files, generate
model_folder = 'xxx/yyy/117M'
config_path = os.path.join(model_folder, 'hparams.json')
checkpoint_path = os.path.join(model_folder, 'model.ckpt')
encoder_path = os.path.join(model_folder, 'encoder.json')
vocab_path = os.path.join(model_folder, 'vocab.bpe')
print('Load model from checkpoint...')
model = load_trained_model_from_checkpoint(config_path, checkpoint_path)
print('Load BPE from files...')
bpe = get_bpe_from_files(encoder_path, vocab_path)
print('Generate text...')
output = generate(model, bpe, ['From the day forth, my arm'], length=20, top_k=1)
# If you are using the 117M model and top_k equals to 1, then the result will be:
# "From the day forth, my arm was broken, and I was in a state of pain. I was in a state of pain,"
print(output[0])