Popular GitHub Repositories for Cache Efficiency

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

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）

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

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

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

??Maximize your efficiency and productivity, support for English,中文,Espa?ol,???????. 让生产力加倍的AI快捷指令。更有效地定制、保存和分享自己的提示词。在提示词分享社区中，轻松找到适用于不同场景的指令。

Supercharge Your Model Training

Supercharge Your LLM with the Fastest KV Cache Layer

Scalable Multi-modal RAG platform

?? Lobe theme - The modern theme for stable diffusion webui, exquisite interface design, highly customizable UI, and efficiency boosting features.

High-efficiency floating-point neural network inference operators for mobile, server, and Web

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

Fluid, elastic data abstraction and acceleration for BigData/AI applications in cloud. (Project under CNCF)

This is a collection of our NAS and Vision Transformer work.

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

Rigourous evaluation of LLM-synthesized code - NeurIPS 2023 & COLM 2024

AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen? and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency.

Unified KV Cache Compression Methods for Auto-Regressive Models

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

R-KV: Redundancy-aware KV Cache Compression for Reasoning Models