Hugging Face Code Samples

Welcome to the repository dedicated to teaching you how to leverage the power of Hugging Face through code samples!

What is Hugging Face?

Hugging Face is an organization that's on a mission to democratize Artificial Intelligence (AI) through natural language processing (NLP). Their libraries, like Transformers and Datasets, have become the de-facto standards for training and deploying state-of-the-art NLP models. Whether it's BERT, GPT-2, T5, or any other popular model, chances are that Hugging Face has an easy-to-use implementation of it.

Why is Hugging Face Important for Developers?

• State-of-the-Art Models: Access to the latest NLP models, pre-trained and ready to deploy.
• Ease of Use: Simple interfaces to tokenize, train, and evaluate models.
• Community-Driven: The Hugging Face model hub allows sharing and using models from the community.
• Broad Framework Support: Hugging Face supports popular ML frameworks like PyTorch and TensorFlow.
• Scalable: Whether you're prototyping on your local machine or deploying in a production environment, Hugging Face is designed to scale.

Table of Contents

1. Beginner

   • The Basics .. coming soon

2. Intermediate .. coming soon

3. Advanced ... coming soon

Contributing

We'd love for you to contribute to this repository and help make it even better! Here's how you can help:

1. Fork the Repository: Click on the 'Fork' button at the top right corner of this page.
2. Clone Your Fork: Open your terminal and run: git clone https://github.com/YOUR_USERNAME/HuggingFace-Code-Samples.git
3. Create a New Branch: Navigate to your local repository and run: git checkout -b new-feature
4. Make Your Changes: Add or edit code samples.
5. Commit and Push: Once you're satisfied with your changes, push them to your fork.
6. Open a Pull Request: Go to this repository and click on 'New Pull Request'. Choose the branch you just pushed to your fork and submit the PR!

Before submitting your pull request, please make sure:

• Your code samples are well-commented and clear.
• You've tested your code to ensure it runs without errors.
• You've updated any relevant documentation or added comments.

Feedback and Issues

If you find any issues or would like to provide feedback, please open an issue or submit a pull request.

Thank you for your interest in this repository! We hope these code samples help you on your NLP journey with Hugging Face.