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, dq
labml.ai's collection of deep learning papers implemented in PyTorch, with the explanation printed alongside the code — transformers, diffusion, RL, optimisers and more.
From the README
pip install labml-nn
- Denoising Diffusion Probabilistic Models (DDPM)
- Denoising Diffusion Implicit Models (DDIM)
- Latent Diffusion Models
- Stable Diffusion
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
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Free · no card · unsubscribe anytime🧑🏫 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, dq
annotated_deep_learning_paper_implementations has 67.1k stars on GitHub. It has been forked 6.7k times. annotated_deep_learning_paper_implementations is written mainly in Python. It has been in active development since 2020. annotated_deep_learning_paper_implementations is available under the MIT license. Its main topics are attention, deep-learning, deep-learning-tutorial, gan.
Read the full guideWhat is 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, dq
Is annotated_deep_learning_paper_implementations open source?
annotated_deep_learning_paper_implementations is an open-source project. It is released under the MIT license.
Is annotated_deep_learning_paper_implementations free?
Yes. annotated_deep_learning_paper_implementations is free and open source — you can use, modify and self-host it.
What license does annotated_deep_learning_paper_implementations use?
annotated_deep_learning_paper_implementations is available under the MIT license.
What language is annotated_deep_learning_paper_implementations written in?
annotated_deep_learning_paper_implementations is written mainly in Python.
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