This project is a template for building a chatbot using TypeScript and Next.js, powered by the Hugging Face API. With this template, you can quickly set up a chatbot that uses the Open Assistant SFT-4 12B model to answer various questions and engage in conversations on different topics.
Welcome to a simple chatbot application using Hugging Face and Next.js. This application provides a basic user interface for users to interact with the Open Assistant SFT-4 12B model. With just a few clicks you can chat with a fine-tuned English language model designed for conversation.
Here are some key features of the application:
- 🤖 Easy-to-use chat interface
- 🚀 Quick and responsive
- 🤪 Fun to chat with!
Hugging Face is a company that develops tools for building applications using machine learning. It is most notable for its 🤖 Transformers Python library built for natural language processing applications and its platform that allows users to share machine learning models and datasets.
The model in the example is Open Assistant SFT-4 12B. This is the 4th iteration English supervised-fine-tuning (SFT) model of the Open-Assistant project. It is based on a Pythia 12B that was fine-tuned on human demonstrations of assistant conversations collected through the Open Assistant human feedback web app before March 25, 2023.
To run the example locally you need to:
- Sign up at Hugging Face.
- Go to your Hugging Face account settings. Create a User Access Token with
write
access. - Set the required Hugging Face environment variable with the token as shown the example env file but in a new file called
.env.local
. - Clone the repository,
git clone https://github.com/ElonMusk2002/chat-huggingface.git
- Install the required dependencies with
npm install
- Launch the development server with
npm dev
If you want to contribute to this project, feel free to open a pull request or an issue on GitHub. Before submitting any changes, please make sure you follow these guidelines:
- Check if someone else has already reported the same issue or suggested the same improvement.
- Create a new branch for your changes and use descriptive branch names.
- Write clear commit messages and add comments to your code.
- Make sure your changes are properly tested.
- Update the documentation if necessary.
Thank you for your contributions!