Popular GitHub Repositories for Guided Object Inference Slicing

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

YOLOv5 ? in PyTorch > ONNX > CoreML > TFLite

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

Port of OpenAI's Whisper model in C/C++

Making large AI models cheaper, faster and more accessible

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A generative speech model for daily dialogue.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

OpenMMLab Detection Toolbox and Benchmark

Cross-platform, customizable ML solutions for live and streaming media.

SoftVC VITS Singing Voice Conversion

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

deep learning for image processing including classification and object-detection etc.

Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.

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

CVPR 2025 论文和开源项目合集

本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services