The Hugging Face Diffusion Models Course provides course materials for studying diffusion theory and image generation.
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This interactive visualization teaches how transformer language models work.
About opensource
Transformer Explainer is an interactive visualization tool for learning how Transformer-based models like GPT work. It runs a live GPT-2 model in the browser, where users can enter their own text and observe how internal components and operations work together to predict next tokens.
The project is open source under the MIT License and can also be run locally. Local use requires Node.js v20 or higher and NPM v10 or higher.
Key features
- Runs a live GPT-2 model in the browser
- Accepts user-entered text for experimentation
- Shows internal components working to predict next tokens
- Supports local setup with Node.js and npm
Best for: People learning how Transformer-based models like GPT predict text.
Good for
- Runs a live model in the browser for direct experimentation
- Open source under the MIT License
- Includes a live demo and local setup instructions
Watch out for
- Local setup requires Node.js v20 or higher and NPM v10 or higher
opensource at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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opensource FAQ
How can I try Transformer Explainer?
Use the live demo at http://poloclub.github.io/transformer-explainer.
How do I run it locally?
Clone the repository, run npm install and npm run dev, then open http://localhost:5173 in a browser. Requires Node.js v20 or higher and NPM v10 or higher.
What license does it use?
MIT License.
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