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 are actively maintaining this repo and adding new implementations almost weekly. for updates.
Transformers module contains implementations for multi-headed attention and relative multi-headed attention.
- GPT Architecture
- kNN-LM: Generalization through Memorization
- Feedback Transformer
- Switch Transformer
✨ LSTM
- Proximal Policy Optimization with Generalized Advantage Estimation
- Deep Q Networks with with Dueling Network, Prioritized Replay and Double Q Network.
pip install labml_nn
If you use LabML for academic research, please cite the library using the following BibTeX entry.
@misc{labml,
author = {Varuna Jayasiri, Nipun Wijerathne},
title = {LabML: A library to organize machine learning experiments},
year = {2020},
url = {https://lab-ml.com/},
}