Awesome-LLM-RAG: a curated list of advanced retrieval augmented generation (RAG) in Large Language Models

The official Github repository for paper "R^2AG: Incorporating Retrieval Information into Retrieval Augmented Generation" (EMNLP 2024 Findings).

⚡FlashRAG: A Python Toolkit for Efficient RAG Research

open-source code for paper: Retrieval Head Mechanistically Explains Long-Context Factuality

Efficient Triton Kernels for LLM Training

Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀

中文 NLP 预处理、解析工具包，准确、高效、易用 A Chinese NLP Preprocessing & Parsing Package www.jionlp.com

Code of ACL 2024 Findings paper: Towards Better Utilization of Multi-Reference Training Data for Chinese Grammatical Error Correction

LLM101n: Let's build a Storyteller 中文版

（撰写ing..)本仓库偏教程性质，以「模型中文化」为一个典型的模型训练问题切入场景，指导读者上手学习LLM二次微调训练。

An open-source cross-platform alternative to AirDrop

基于 Go 的文件分享工具，仅单可执行文件，开箱即用，内置图床和视频播放页面. File sharing tool based on Go.

「Java学习+面试指南」一份涵盖大部分 Java 程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

📄 适合中文的简历模板收集（LaTeX，HTML/JS and so on）由 @hoochanlon 维护

Code & Data for our Paper "Chinese Grammatical Error Correction via Large Language Model Guided Optimization Training" (CCL2024)

Official Implementation of "Probing Language Models for Pre-training Data Detection"

[IJCAI'19] Code for "Self-attentive Biaffine Dependency Parsing"

Source code of paper "Alirector: Alignment-Enhanced Chinese Grammatical Error Corrector" (Findings of ACL 2024)

Align Anything: Training All-modality Model with Feedback

A one-stop data processing system to make data higher-quality, juicier, and more digestible for (multimodal) LLMs! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大模型提供更高质量、更丰富、更易”消化“的数据！

Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

A vuepress theme with tons of features✨

Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.

A 4-hour coding workshop to understand how LLMs are implemented and used

Evaluation of speculative inference over multilingual tasks

Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**

[ICML2024 (Oral)] Official PyTorch implementation of DoRA: Weight-Decomposed Low-Rank Adaptation