A large collection of ready-made LLM apps: agents, RAG systems and skills for coding agents. Every template can be run and taken apart piece by piece.
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Awesome lists & learninglabmlai
annotated_deep_learning_paper_implementations
More than 60 PyTorch implementations of research papers with notes next to the code: transformers, optimizers, GANs, reinforcement learning. The website shows code and notes side by side.
Who it is for
For people who read deep learning papers and want to see an idea turn into code.
How to start
- Open nn.labml.ai and pick a paper, for example transformers
- Read the code together with the notes beside it
- Install the package to run the code:
pip install labml-nn
Steps are taken from the README. Check the current version in the repository before running them.
Stars over the last 30 days
+211Sep 6 — Oct 6
Author's description
🧑🏫 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, ... 🧠
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