jasonzdeng

jasonzdeng's Stars

• Significant-Gravitas/AutoGPT

  AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

  Language:Python169k1.5k2.9k44.5k

• f/awesome-chatgpt-prompts

  This repo includes ChatGPT prompt curation to use ChatGPT better.

  Language:HTML113k1.5k015.5k

• langchain-ai/langchain

  🦜🔗 Build context-aware reasoning applications

  Language:Jupyter Notebook95.4k6927.9k15.5k

• meta-llama/llama

  Inference code for Llama models

  Language:Python56.6k5261k9.6k

• microsoft/DeepSpeed

  DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

  Language:Python35.6k3452.8k4.1k

• openai/openai-python

  The official Python library for the OpenAI API

  Language:Python23.2k3088103.3k

• jcjohnson/neural-style

  Torch implementation of neural style algorithm

  Language:Lua18.3k6354392.7k

• google-deepmind/alphafold

  Open source code for AlphaFold 2.

  Language:Python12.9k2288642.3k

• RosettaCommons/RFdiffusion

  Code for running RFdiffusion

  Language:Python1.8k42207349

• gcorso/DiffDock

  Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

  Language:Python1.1k18231265

• baker-laboratory/RoseTTAFold-All-Atom

  Language:Python65211126118

• gnina/gnina

  A deep learning framework for molecular docking

  Language:C++63831215147

• divelab/AIRS

  Artificial Intelligence Research for Science (AIRS)

  Language:Python529181761

• luwei0917/DynamicBind

  repo for DynamicBind: Predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model

  Language:Jupyter Notebook20273844

• uw-ipd/RoseTTAFold2

  Language:Python17863039

• bjing2016/EigenFold

  EigenFold: Generative Protein Structure Prediction with Diffusion Models

  Language:Jupyter Notebook1657526

• rxn4chemistry/rxnfp

  Reaction fingerprints, atlases and classification. Code complementing our Nature Machine Intelligence publication on "Mapping the space of chemical reactions using attention-based neural networks" (http://rdcu.be/cenmd).

  Language:HTML15891641

• basf/MolPipeline

  A Python package for processing molecules with RDKit in scikit-learn

  Language:Python1526469

• MolecularAI/deep-molecular-optimization

  Molecular optimization by capturing chemist’s intuition using the Seq2Seq with attention and the Transformer

  Language:Python1447039

• aqlaboratory/rgn2

  Language:Python101111129

• Exscientia/molflux

  A foundational package for molecular predictive modelling

  Language:Python877511

• CellProfiler/tutorials

  CellProfiler tutorial pipelines and images

  Language:Jupyter Notebook84101986

• gnina/models

  Trained caffe models

  Language:Python8252823

• shuyana/DiffusionProteinLigand

  Language:Python773611

• biomap-research/xTrimoMultimer

  Language:Python7481016

• mims-harvard/PINNACLE

  Contextual AI models for single-cell protein biology

  Language:Python713418

• coleygroup/QM-augmented_GNN

  Language:Python18213

• amp91/PeptideModels

  Code for peptide ligand design with machine learning models.

  Language:Python16204

• CBIIT/GGMD

  Language:Python5504

• jensengroup/RegioSQM20

  RegioSQM20 predicts the regioselectivity of electrophilic aromatic substitution reactions in heteroaromatic systems.

  Language:Python5305