https://github.com/e-tornike/Story_Generator

A Streamlit web app that generates Rick and Morty stories using GPT2.
https://github.com/e-tornike/Story_Generator

gpt2 huggingface-transformers machine-learning natural-language-processing streamlit

Last synced: about 2 months ago
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A Streamlit web app that generates Rick and Morty stories using GPT2.

• Host: GitHub
• URL: https://github.com/e-tornike/Story_Generator
• Owner: e-tornike
• License: mit
• Archived: true
• Created: 2020-10-26T20:53:41.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2023-02-20T10:11:58.000Z (almost 2 years ago)
• Last Synced: 2024-10-31T13:33:02.460Z (2 months ago)
• Topics: gpt2, huggingface-transformers, machine-learning, natural-language-processing, streamlit
• Language: Python
• Homepage: https://share.streamlit.io/e-tony/story_generator/main/app.py
• Size: 296 KB
• Stars: 40
• Watchers: 1
• Forks: 8
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
# Rick and Morty Story Generator

[![Open in Streamlit](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/e-tony/story_generator/main/app.py)

This project uses a [pre-trained GPT2 model](https://huggingface.co/gpt2), which was fine-tuned on [Rick and Morty transcripts](https://rickandmorty.fandom.com/wiki/Category:Transcripts), to generate new stories in the form of a dialog. The project uses Hugging Face's [Transformers library](https://github.com/huggingface/transformers) to do inference and [Streamlit](https://www.streamlit.io/) for the application. 

Try out the [demo](https://share.streamlit.io/e-tony/story_generator/main/app.py) to generate fun stories or read the blog [post](https://towardsdatascience.com/rick-and-morty-story-generation-with-gpt2-using-transformers-and-streamlit-in-57-lines-of-code-8f81a8f92692) on how to create your own story generator.

### Fine-tuning a custom model

You can fine-tune your own model using Google Colab [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1opXtwhZ02DjdyoVlafiF3Niec4GqPJvC?usp=sharing)

### Setup

This repository has only been tested with Python 3.7. 

Install the dependencies in a virtual environment:

```

python3.7 -m venv venv

source venv/bin/activate

pip install --upgrade pip setuptools

pip install -r requirements.txt

```

On the first run, the app will download the pre-trained model from Hugging Face's Model Hub or you can supply your own custom model in the `load_model()` function. To start the application, simply run:

```

streamlit run app.py

```