Popular GitHub Repositories for Flexibility

Burn is a new comprehensive dynamic Deep Learning Framework built using Rust with extreme flexibility, compute efficiency and portability as its primary goals.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

Flax is a neural network library for JAX that is designed for flexibility.

A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility

A lightweight task engine for building stateful AI agents that prioritizes simplicity and flexibility.

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

High-performance inference framework for large language models, focusing on efficiency, flexibility, and availability.

A lightweight task engine for building stateful AI agents that prioritizes simplicity and flexibility.

Paddle Multimodal Integration and eXploration, supporting mainstream multi-modal tasks, including end-to-end large-scale multi-modal pretrain models and diffusion model toolbox. Equipped with high performance and flexibility.

An On-Chain Open-Source Platform for Rapid AI Model Productization Using Decentralized Resources with Flexibility and Scalability

Implementation of Classifier Free Guidance in Pytorch, with emphasis on text conditioning, and flexibility to include multiple text embedding models

An open-source, code-first Java toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

6 nodes for ComfyUI that allows for more control and flexibility over noise to do e.g. variations or "un-sampling"

Transforms your CasADi functions into batchable JAX-compatible functions. By combining the power of CasADi with the flexibility of JAX, JAXADi enables the creation of efficient code that runs smoothly on CPUs, GPUs, and TPUs.

An On-Chain Open-Source Platform for Rapid AI Model Productization Using Decentralized Resources with Flexibility and Scalability

Multi-domain Distribution Learning for De Novo Drug Design

? A fast Adaptive Machine Learning library for Time-Series, that lets you build, deploy and update composite models easily. An order of magnitude speed-up, combined with flexibility and rigour. This is an internal project - documentation is not updated anymore and substantially differ from the current API.

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

A neural network training interface based on PyTorch, with a focus on flexibility

Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system.