Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Core deep-learning frameworks and libraries for pretraining and distributed training.
Signals: deep-learning, neural-network, pytorch, tensorflow, jax, distributed-training, training, deepspeed
2,697 results
SeisBench - A toolbox for machine learning in seismology
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
DeepTab is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mambular, TabM, FT-Transformer, TabulaRNN, TabTransformer, and tabular ResNets.
SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.
Machine learning metrics for distributed, scalable PyTorch applications.
docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning. Ongoing development and maintenance by t2k.
An extension of Open3D to address 3D Machine Learning tasks
A scikit-learn compatible neural network library that wraps PyTorch
Compact and Agent-Native MoE Training System
slime is an LLM post-training framework for RL Scaling.
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
Rumale is a machine learning library in Ruby
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Machine learning algorithms for many-body quantum systems
Clair3 - Symphonizing pileup and full-alignment for deep learning-based long-read variant calling
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
OpenNN - Open Neural Networks Library
On-device AI across mobile, embedded and edge for PyTorch
Efficiently computes derivatives of NumPy code.
ModelScope: bring the notion of Model-as-a-Service to life.
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
Medical imaging processing for AI applications.
24,523 repositories in the index in total.
