https://github.com/trbndev/wikibert

👨🏻‍🏫🚧 Experiment: Training a Neural Network with Wikipedia Articles
https://github.com/trbndev/wikibert

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👨🏻‍🏫🚧 Experiment: Training a Neural Network with Wikipedia Articles

• Host: GitHub
• URL: https://github.com/trbndev/wikibert
• Owner: trbndev
• Created: 2024-12-15T15:21:42.000Z (10 days ago)
• Default Branch: main
• Last Pushed: 2024-12-15T15:30:26.000Z (10 days ago)
• Last Synced: 2024-12-15T16:30:20.891Z (10 days ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 4.66 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 👨🏻‍🏫 Wikibert

This is an experimental weekend project for testing purposes.

## 📝 Overview

**Wikibert** is a project that demonstrates text generation using Wikipedia data. It consists of two main components:

- 🐍 A Python script (`get_data.py`) for fetching and saving Wikipedia pages.

- 📓 A Jupyter notebook (`wikibert.ipynb`) for training a text generation model using TensorFlow.

## 🛠️ get_data.py

The `get_data.py` script performs the following tasks:

- 🔄 Fetches a Wikipedia page and its linked pages recursively up to a specified depth.

- 💾 Saves the content of each page into individual text files in a `data` folder.

- 🧹 Sanitizes filenames to ensure compatibility with the file system.

## 📊 wikibert.ipynb

The `wikibert.ipynb` notebook includes the following steps:

- 🔍 Loads and preprocesses text data from the saved Wikipedia pages.

- 🏗️ Builds and trains a GRU-based RNN model for text generation using TensorFlow.

- 💾 Saves model checkpoints during training.

- 📝 Generates text using the trained model.

## 🚀 Usage

1. Run `get_data.py` to fetch and save Wikipedia pages.

2. Open `wikibert.ipynb` in Jupyter Notebook or Google Colab.

3. Follow the cells in the notebook to train the text generation model and generate text.

## 📋 Requirements

- Python 3.x

- `wikipedia-api` library

- TensorFlow

- Jupyter Notebook (for `wikibert.ipynb`)

## 🛠️ Installation

Install the required libraries using pip:

```bash

pip install wikipedia-api tensorflow

```

## 📄 License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.