🎓 系统性大语言模型构建课程｜🛠️ 覆盖预训练数据工程、Tokenizer、Transformer、MoE、GPU 编程 (CUDA/Triton)、分布式训练、Scaling Laws、推理优化及对齐 (SFT/RLHF/GRPO)｜🚀 6 个渐进式作业 + 代码驱动，建立 LLM 全栈认知体系

Minimal reproduction of OneRec

《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程

所有小初高、大学PDF教材。

🚀🚀 「大模型」2小时完全从0训练26M的小参数GPT！🌏 Train a 26M-parameter GPT from scratch in just 2h!

The best ChatGPT that $100 can buy.

A course on aligning smol models.

The code for paper

📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉

GRID: Generative Recommendation with Semantic IDs

Awesome Generative Recommendation papers primarily focused on industry-level applications.

Awesome things about generative recommendation models.

High-performance inference framework for large language models, focusing on efficiency, flexibility, and availability.

Pytorch🍊🍉 is delicious, just eat it! 😋😋

This is the repo for the survey of LLM4IR.

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

Repository hosting code used to reproduce results in "Actions Speak Louder than Words Trillion-Parameter Sequential Transducers for Generative Recommendations" (https://arxiv.org/abs/2402.17152).

Papers and resources about POI recommendation. | 兴趣点推荐相关论文、模型和资源。

Large Language Model-enhanced Recommender System Papers

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

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.

Stanford CS149 - Programming Assignment 5 (Extra Credit)

Hands-On Graph Neural Networks Using Python, published by Packt

搜索引擎原理

Making large AI models cheaper, faster and more accessible

A playbook for systematically maximizing the performance of deep learning models.

教科书《计算机体系结构基础》（胡伟武等，第三版）的开源版本