Stars
🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
C++ and Python implementations of YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOv11 inference.
🤖 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, transf…
Aila(AI超元域): The premier AI integration tool for Windows, macOS, and Android. Ask once, get answers from 10+ AIs like ChatGPT, Gemini, Claude3, Copilot, Poe, perplexity and more. Features customiza…
🔥 全网首发,mmdetection Co-DETR TensorRT端到端推理加速
[CVPR 2024] SHViT: Single-Head Vision Transformer with Memory Efficient Macro Design
面向开发者的 LLM 入门教程,吴恩达大模型系列课程中文版
[NeurIPS 2024 🔥] DI-MaskDINO: A Joint Object Detection and Instance Segmentation Model
Converting COCO annotation (CVAT) to annotation for YOLO-seg (instance segmentation) and YOLO-obb (oriented bounding box detection)
Python library for YOLO small object detection and instance segmentation
Build a RAG (Retrieval Augmented Generation) pipeline from scratch and have it all run locally.
This will be a walk through of select code samples of the book "Transformers for Natural Language Processing and Computer Vision" 3rd Edition by Denis Rothman
《Pytorch实用教程》(第二版)无论是零基础入门,还是CV、NLP、LLM项目应用,或是进阶工程化部署落地,在这里都有。相信在本书的帮助下,读者将能够轻松掌握 PyTorch 的使用,成为一名优秀的深度学习工程师。
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
Understanding Deep Learning - Simon J.D. Prince
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
Jupyter notebook tutorials for MMPretrain
中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
A Python library to extract tabular data from PDFs
《Machine Learning Systems: Design and Implementation》- Chinese Version
AISystem 主要是指AI系统,包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
🤖 PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+