readme.md

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    labml.ai Deep Learning Paper Implementations

    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.

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    We are actively maintaining this repo and adding new implementations almost weekly. Twitter for updates.

    Paper Implementations

    Transformers

    Eleuther GPT-NeoX

    Diffusion models

    Generative Adversarial Networks

    Recurrent Highway Networks

    LSTM

    HyperNetworks - HyperLSTM

    ResNet

    ConvMixer

    Capsule Networks

    U-Net

    Sketch RNN

    Graph Neural Networks

    Counterfactual Regret Minimization (CFR)

    Solving games with incomplete information such as poker with CFR.

    Reinforcement Learning

    Optimizers

    Normalization Layers

    Distillation

    Adaptive Computation

    Uncertainty

    Activations

    Langauge Model Sampling Techniques

    Scalable Training/Inference

    Highlighted Research Paper PDFs

    Installation

    pip install labml-nn

    Citing

    If you use this for academic research, please cite it using the following BibTeX entry.

    @misc{labml,
     author = {Varuna Jayasiri, Nipun Wijerathne},
     title = {labml.ai Annotated Paper Implementations},
     year = {2020},
     url = {https://nn.labml.ai/},
    }

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    This shows the most popular research papers on social media. It also aggregates links to useful resources like paper explanations videos and discussions.

    🧪 labml.ai/labml

    This is a library that let's you monitor deep learning model training and hardware usage from your mobile phone. It also comes with a bunch of other tools to help write deep learning code efficiently.

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    开发语言

    • Jupyter Notebook 54.8 %
    • Python 45.1 %
    • Makefile 0.1 %