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🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
scikit-learn: machine learning in Python
Official Code for DragGAN (SIGGRAPH 2023)
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
⚡ A Fast, Extensible Progress Bar for Python and CLI
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Train transformer language models with reinforcement learning.
StyleGAN - Official TensorFlow Implementation
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Open source code for AlphaFold 2.
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are commi…
Kronos: A Foundation Model for the Language of Financial Markets
Official PyTorch implementation of StyleGAN3
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Official git repository for Biopython (originally converted from CVS)
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)
Official repository for the Boltz biomolecular interaction models
深度学习与PyTorch入门实战视频教程 配套源代码和PPT
A PyTorch Library for Multi-Task Learning
Message Passing Neural Networks for Molecule Property Prediction
To eventually become an unofficial Pytorch implementation / replication of Alphafold2, as details of the architecture get released
Implementation of Alphafold 3 from Google Deepmind in Pytorch
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
⚡VoltaML is a lightweight library to convert and run your ML/DL deep learning models in high performance inference runtimes like TensorRT, TorchScript, ONNX and TVM.