Popular GitHub Repositories for High Preformance

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

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/

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

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

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

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.

High-performance In-browser LLM Inference Engine

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

A platform to build and run apps that are elastic, agile, and resilient. SDK, libraries, and hosted environments.

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.

Create and run high-performance macOS and Linux VMs on Apple Silicon, with built-in support for AI agents.

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

YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/

Refine high-quality datasets and visual AI models

Build, Manage and Deploy AI/ML Systems

? LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through our open source R&D automation tool RD-Agent, which lets AI drive data-driven AI.