large-language-models

Official code for NeurIPS2025 "Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers"

[NeurIPS 2024] This repo contains evaluation code for the paper "Are We on the Right Way for Evaluating Large Vision-Language Models"

Open Source AI Tracing Framework built on Opentelemetry for AI Applications and Frameworks

🚀 200倍速！AI时代的下载神器 | Docker/PyPI/HuggingFace/CRAN 全加速 | 并行分片+智能缓存，让下载飞起来

Open-source versioning, tracing, and annotation tooling.

Visualization for a Retrieval-Augmented Generation (RAG) Assistant 🤖❤️📚

Developed an AI application using LLM to analyze user resumes and provided the summarization, strengths, weaknesses, suggestions, suitable job titles, and also scraping job details from LinkedIn using Selenium. This application reduces time by 30% and helps candidates tailor their resumes effectively.

Complex question answering in LLMs with enhanced reasoning and information-seeking capabilities.

A curated list of battle-tested tools, frameworks, and best practices for building scalable, production-grade Retrieval-Augmented Generation (RAG) systems.

Humanable Chat Generative-model Fine-tuning | LLM微调

[ICLR'26] AutoGEO: a Generative Engine Optimization framework to automatically learn generative engine preferences, and rewrite web contents for more traction.

Collection of free Notes,Courses,Videos,Projects,Articles and Repos Links To learn Machine learning ,Deep learning,Python,SQL,CNN,NLP,GAN,GNN,Transfomers,Flask,Django,and End to End Machine learning Projects

A guide to LLM hacking: fundamentals, prompt injection, offense, and defense

从 MiniMind 源码读起,再延伸到现代大模型技术体系的中文学习笔记。主线逐行精读预训练 / SFT / DPO / PPO / GRPO 与训练机制;附录 17 篇进阶卷覆盖量化、投机解码、RLHF 全景、模型代际史等 MiniMind 没涉及、但进阶绕不开的主题。

A collection of prompts for use with GPT-4 via ChatGPT, OpenAI API w/ Gradio frontend & notebook

This framework works as a form of user/machine calibration, with a focus on user-context and user-intent, deconstructing your ideas logically from A to B to Z.

A pure-Python context management layer for LLM systems — retrieval, re-ranking, memory decay, and token-budget enforcement in one pipeline.

A prompting library

Embed arbitrary modalities (images, audio, documents, etc) into large language models.

A Python toolkit for chain-of-thought prompting 🐍