labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
[](https://twitter.com/labmlai) Note: use the Annotated Implementation Skill with coding agents to implement any paper. This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better. We…
Read the full README ↗ · Preview checked 2026-10-30T15:47:00.364Z
Inside the original README — Document outline
- labml.ai Deep Learning Paper Implementations
- Paper Implementations
- ✨ Transformers
- ✨ Low-Rank Adaptation (LoRA)
- ✨ Eleuther GPT-NeoX
- ✨ Diffusion models
- ✨ Generative Adversarial Networks
- ✨ Recurrent Highway Networks
- ✨ LSTM
- ✨ HyperNetworks - HyperLSTM
- ✨ ResNet
- ✨ ConvMixer
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Documentation belongs to its respective authors. Reported project/model license: MIT. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Repository facts
- Owner
- labmlai
- Primary language
- Python
- Stars
- 67,616
- Forks
- 6,779
- Open issues + pull requests
- 46
- License
- MIT
- Archived
- No
- Default branch
- master
- Created
- 2020-08-25T02:29:34.000Z
- Last push
- 2026-10-25T17:01:15.000Z
Topics and intended use
Owner-supplied topics: attention, deep-learning, deep-learning-tutorial, gan, literate-programming, lora, machine-learning, neural-networks, optimizers, pytorch, reinforcement-learning, transformer, transformers
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
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Source and freshness
Source: GitHub. Metadata observed 2026-10-31T12:19:22.904Z. Daily imports are snapshots, not real-time monitoring.
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