hyunwoongko/transformer resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

4645 stars · 642 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A from-scratch PyTorch implementation of the Transformer model from the paper 'Attention Is All You Need', written for educational purposes. It includes readable implementations of positional encoding, multi-head attention, and other core Transformer components.

Use cases

• learn how the transformer architecture works internally
• understand multi-head attention with code
• study positional encoding implementation in pytorch
• reference implementation of attention is all you need
• teach transformer concepts with a minimal codebase

When to choose

• you want to read a simple, annotated implementation of the Transformer to learn the architecture
• you need a small educational codebase rather than a production library

When to avoid

• you need a production-grade, well-tested Transformer implementation (use Hugging Face Transformers or PyTorch's built-in nn.Transformer)
• you need ongoing maintenance or bug-free guarantees - the author explicitly warns the code is not well maintained

Facets

learning-resource · maturity maintenance

deep-learning machine-learning deep-learning tutorials python transformer attention pytorch-implementation educational attention-is-all-you-need natural-language-processing

Member repositories

For agents

markdown · JSON · MCP: product_card(name="hyunwoongko/transformer")