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        "description": "# Keras GPT-2\n\n[![Version](https://img.shields.io/pypi/v/keras-gpt-2.svg)](https://pypi.org/project/keras-gpt-2/)\n![License](https://img.shields.io/pypi/l/keras-gpt-2.svg)\n\n\\[[\u4e2d\u6587](https://github.com/CyberZHG/keras-gpt-2/blob/master/README.zh-CN.md)|[English](https://github.com/CyberZHG/keras-gpt-2/blob/master/README.md)\\]\n\nLoad pretrained weights and predict with [GPT-2](https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf).\n\n## Install\n\n```bash\npip install keras-gpt-2\n```\n\n## Demo\n\n```python\nimport os\nfrom keras_gpt_2 import load_trained_model_from_checkpoint, get_bpe_from_files, generate\n\n\nmodel_folder = 'xxx/yyy/117M'\nconfig_path = os.path.join(model_folder, 'hparams.json')\ncheckpoint_path = os.path.join(model_folder, 'model.ckpt')\nencoder_path = os.path.join(model_folder, 'encoder.json')\nvocab_path = os.path.join(model_folder, 'vocab.bpe')\n\n\nprint('Load model from checkpoint...')\nmodel = load_trained_model_from_checkpoint(config_path, checkpoint_path)\nprint('Load BPE from files...')\nbpe = get_bpe_from_files(encoder_path, vocab_path)\nprint('Generate text...')\noutput = generate(model, bpe, ['From the day forth, my arm'], length=20, top_k=1)\n\n# If you are using the 117M model and top_k equals to 1, then the result will be:\n# \"From the day forth, my arm was broken, and I was in a state of pain. I was in a state of pain,\"\nprint(output[0])\n```",
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