setup.py

from setuptools import setup

long_description = """
A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI GPT-2 text generation model (specifically the "small", 124M hyperparameter version). Additionally, this package allows easier generation of text, generating to a file for easy curation, allowing for prefixes to force the text to start with a given phrase.

## Usage

An example for downloading the model to the local system, fineturning it on a dataset. and generating some text.

Warning: the pretrained model, and thus any finetuned model, is 500 MB!

```python
import gpt_2_simple as gpt2

gpt2.download_gpt2()   # model is saved into current directory under /models/124M/

sess = gpt2.start_tf_sess()
gpt2.finetune(sess, 'shakespeare.txt', steps=1000)   # steps is max number of training steps

gpt2.generate(sess)
```

The generated model checkpoints are by default in `/checkpoint/run1`. If you want to load a model from that folder and generate text from it:

```python
import gpt_2_simple as gpt2

sess = gpt2.start_tf_sess()
gpt2.load_gpt2(sess)

gpt2.generate(sess)
```

As with textgenrnn, you can generate and save text for later use (e.g. an API or a bot) by using the `return_as_list` parameter.

```python
single_text = gpt2.generate(sess, return_as_list=True)[0]
print(single_text)
```

You can pass a `run_name` parameter to `finetune` and `load_gpt2` if you want to store/load multiple models in a `checkpoint` folder.

NB: *Restart the Python session first* if you want to finetune on another dataset or load another model.
"""


setup(
    name="gpt_2_simple",
    packages=["gpt_2_simple"],  # this must be the same as the name above
    version="0.8.1",
    description="Python package to easily retrain OpenAI's GPT-2 "
    "text-generating model on new texts.",
    long_description=long_description,
    long_description_content_type="text/markdown",
    author="Max Woolf",
    author_email="max@minimaxir.com",
    url="https://github.com/minimaxir/gpt-2-simple",
    keywords=["deep learning", "tensorflow", "text generation"],
    classifiers=[],
    license="MIT",
    entry_points={
        "console_scripts": ["gpt_2_simple=gpt_2_simple.gpt_2:cmd"],
    },
    python_requires=">=3.6",
    include_package_data=True,
    install_requires=[
        "tensorflow>=2.5.1",
        "regex",
        "requests",
        "tqdm",
        "numpy",
        "toposort",
    ],
)