Starred repositories
41
results
for source starred repositories
Clear filter
UltraRAG v3: A Low-Code MCP Framework for Building Complex and Innovative RAG Pipelines
Build resilient language agents as graphs.
A minimal Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
This repository contains the official implementation code of NeurIPS 2025 paper: "Instance-Level Composed Image Retrieval".
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
(Unofficial) PyTorch implementation of grouped-query attention (GQA) from "GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints" (https://arxiv.org/pdf/2305.13245.pdf)
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Chinese and English multimodal conversational language model | 多模态中英双语对话语言模型
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
High-Resolution Image Synthesis with Latent Diffusion Models
This is a repo for studying the application of LLM Agents on Games
本项目为Generative Agents项目的重构+深度汉化版本，旨在为中文用户提供一个利于维护的基础版本，以便后续实验或功能拓展。
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
A PyTorch implementation of the Transformer model in "Attention is All You Need".
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Record the process of learning algorithm problems on various platforms and continuously enhance my algorithm ability.
[ICML2023] IRNeXt: Rethinking Convolutional Network Design for Image Restoration
A comprehensive collection of PyTorch tutorials covering essential concepts and applications
AIInfra（AI 基础设施）指AI系统从底层芯片等硬件，到上层软件栈支持AI大模型训练和推理。