Popular GitHub Repositories for High Level Feature

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.

A high-throughput and memory-efficient inference and serving engine for LLMs

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling

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/

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

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

MiniCPM-o 2.6: A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)

High-performance In-browser LLM Inference Engine

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Netflix-level subtitle cutting, translation, alignment, and even dubbing - one-click fully automated AI video subtitle team | Netflix级字幕切割、翻译、对齐、甚至加上配音，一键全自动视频搬运AI字幕组

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

NVIDIA? TensorRT? is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.

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

Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.