Awesome ModelContextProtocol resources - A curated list of MCP resources

[NeurlPS2024] One-Step Effective Diffusion Network for Real-World Image Super-Resolution

Learn System Design concepts and prepare for interviews using free resources.

互联网公司技术架构，微信/淘宝/微博/腾讯/阿里/美团点评/百度/OpenAI/Google/Facebook/Amazon/eBay的架构，欢迎PR补充

Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI

experiments on Paper <Bag of Tricks for Image Classification with Convolutional Neural Networks> and other useful tricks to improve CNN acc

Codebase for Image Classification Research, written in PyTorch.

🏂🏻 程序员海外工作/英文面试手册

推荐系统入门指南，全面介绍了工业级推荐系统的理论知识（王树森推荐系统公开课-基于小红书的场景讲解工业界真实的推荐系统），如何基于TensorFlow2训练模型，如何实现高性能、高并发、高可用的Golang推理微服务。Comprehensively introduced the theory of industrial recommender system, how to trainning …

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型

Official Implementation of Rectified Flow (ICLR2023 Spotlight)

[ICLR 2025] Rectified Diffusion: Straightness Is Not Your Need

Official implementation of "MIMO: Controllable Character Video Synthesis with Spatial Decomposed Modeling"

[CVPR 2024 Highlight] Official repository for the paper "3DGStream: On-the-fly Training of 3D Gaussians for Efficient Streaming of Photo-Realistic Free-Viewpoint Videos".

Official implementation of "ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis"

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…

ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment

Qwen2.5 is the large language model series developed by Qwen team, Alibaba Cloud.

本项目旨在收集开源的表格智能任务数据集（比如表格问答、表格-文本生成等），将原始数据整理为指令微调格式的数据并微调LLM，进而增强LLM对于表格数据的理解，最终构建出专门面向表格智能任务的大型语言模型。

Python package built to ease deep learning on graph, on top of existing DL frameworks.

[EMNLP'23, ACL'24] To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

Mamba SSM architecture

Retrieval and Retrieval-augmented LLMs

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

Grok open release

Code and documentation to train Stanford's Alpaca models, and generate the data.

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 mode…