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An Open Source Machine Learning Framework for Everyone

Tensors and Dynamic neural networks in Python with strong GPU acceleration

💫 Industrial-strength Natural Language Processing (NLP) in Python

Visualizer for neural network, deep learning and machine learning models

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Open standard for machine learning interoperability

Topic Modelling for Humans

Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.

A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!

Low-code framework for building custom LLMs, neural networks, and other AI models

🐍 Geometric Computer Vision Library for Spatial AI

Deep learning library featuring a higher-level API for TensorFlow.

Efficiently computes derivatives of NumPy code.

Deep Learning and Reinforcement Learning Library for Scientists and Engineers

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

Supercharge Your Model Training

Rust bindings for the C++ api of PyTorch.

An Engine-Agnostic Deep Learning Framework in Java

On-device AI across mobile, embedded and edge for PyTorch

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

Scalable and user friendly neural :brain: forecasting algorithms.

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

a delightful machine learning tool that allows you to train, test, and use models without writing code

Distributed LLM inference. Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference.

2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

ML algorithms implemented and derived from first-principles in Jupyter Notebooks and NumPy

A Data Streaming Library for Efficient Neural Network Training