Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward networks. Users can observe how attention weights change as the model predicts the next token, offering insight into how transformer architectures capture relationships between words. The design of the platform emphasizes educational accessibility, allowing students, researchers, and developers to explore complex machine learning concepts without requiring specialized hardware or installations.
Features
- Interactive visualization of transformer architecture components
- Live GPT-2 model execution directly in the browser
- Real-time visualization of token processing and attention patterns
- Educational interface for exploring transformer operations step by step
- Support for experimenting with custom text prompts
- Visual explanations of embeddings, self-attention, and prediction mechanisms