Metadata-Version: 2.1
Name: gpt2-plot
Version: 0.0.4
Summary: Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts.
Home-page: UNKNOWN
Author: yuyu
Author-email: yuyurukia@gmail.com
License: MIT
Keywords: deep learning,tensorflow,text generation
Platform: UNKNOWN
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Requires-Dist: regex
Requires-Dist: requests
Requires-Dist: tqdm
Requires-Dist: numpy
Requires-Dist: toposort


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.


