Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Courses, books, tutorials, paper collections and curated awesome lists.
Signals: awesome, awesome-list, tutorial, course, learning, roadmap, papers, book
1,903 results
My Solution and Notes for the Stanford CS336: LLM from scratch
Obsidian plugins focused on leveraging AI & LLMs inside of (and beyond) vaults
大语言模型(LLM)理论+代码教程，由浅入深，带你系统学习LLM的理论知识并从代码层面理解其如何实现。
The official GitHub page for the survey paper "Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond". And this paper is under review.
markdown file of full pinescript v6 file for LLM's to ingest
A collection of LLM with RL papers
papers related to LLM-agent that published on top conferences
Notes from the Latent Space paper club. Follow along or start your own!
No description
Review automated kernel generation in the era of LLMs
A curated list of LLM Interpretability related material - Tutorial, Library, Survey, Paper, Blog, etc..
A set of lessons aimed at anyone learning LLM and generative AI concepts, with sections on operations and security, as well as development.
OpenLLMWiki: Docs of OpenLLMAI. Survey, reproduction and domain/task adaptation of open source chatgpt alternatives/implementations. PiXiu-貔貅 means fortune.
本项目是一个围绕 DeepLearning.AI 出品的 Post-Training for LLMs 系列课程，为国内学习者量身打造的中文翻译与知识整理教程。项目提供课程内容翻译、知识点梳理和示例代码等内容，旨在降低语言门槛，让更多学生、研究人员和开发者系统掌握大语言模型（LLM）后训练阶段的核心技术与实践方法。
看图学大模型
一些 LLM 方面的从零复现笔记
A category wise collection of 200+ LLM survey papers.
Papers & Works for large languange models (OpenAI GPT-4, Meta Llama, etc.).
📖 从零基础到面试通关 —— 22节课彻底搞懂大语言模型 | Learn MiniMind: 系统化学习LLM训练全流程
This repository serves as a comprehensive survey of LLM development, featuring numerous research papers along with their corresponding code links.
This repository contains a regularly updated paper list for LLMs-reasoning-in-latent-space.
A curated collection of LLM reasoning and planning resources, including key papers, limitations, benchmarks, and additional learning materials.
llm相关内容，包括：基础知识、八股文、面经、经典论文
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