labmlai/annotated_deep_learning_paper_implementations
๐งโ๐ซ 60+ Implementations/tutorials of deep learning papers with side-by-side notes ๐; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga
- Stars
- 68k
- Forks
- 6.8k
- Open issues
- 29
- Last push
- 9mo ago
About annotated_deep_learning_paper_implementations
annotated_deep_learning_paper_implementations is a free, open-source AI resource list by labmlai, written mainly in Python. ๐งโ๐ซ 60+ Implementations/tutorials of deep learning papers with side-by-side notes ๐; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga. It has 68k GitHub stars and 6.8k forks, and was last updated 9mo ago. It's released under the MIT license, a standard open-source license.
- License
- MIT
- Language
- Python
- Stars
- 67,583
- Last update
- 9mo ago
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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annotated_deep_learning_paper_implementations FAQ
Is annotated_deep_learning_paper_implementations free?
Yes. annotated_deep_learning_paper_implementations is open source and free to use. It's released under the MIT license, a standard open-source license.
Does annotated_deep_learning_paper_implementations run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does annotated_deep_learning_paper_implementations need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is annotated_deep_learning_paper_implementations still maintained?
It was last updated 9mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to annotated_deep_learning_paper_implementations?
Similar free, open-source tools include 500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code, x-transformers, CVPR2026-Papers-with-Code, anomaly-detection-resources.