本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.

Scalable data pre processing and curation toolkit for LLMs

A series of math-specific large language models of our Qwen2 series.

PaL: Program-Aided Language Models (ICML 2023)

Tuning LLMs with no tears💦; Sample Design Engineering (SDE) for more efficient downstream-tuning.

a Fine-tuned LLaMA that is Good at Arithmetic Tasks

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

A PyTorch Library for Multi-Task Learning

A curated collection of adversarial attack and defense on recommender systems.

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show an…

RSTutorials: A Curated List of Must-read Papers on Recommender System.

How To Ask Questions The Smart Way 《提问的智慧》中文版

Source code for our EMNLP'21 paper 《Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning》

深度学习相关的模型训练、评估和预测相关代码

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM, xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... （pytorch, tf2.0）

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

数据挖掘、计算机视觉、自然语言处理、推荐系统竞赛知识、代码、思路

主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。

计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

Recommender Learning with Tensorflow2.x

Factorization Machine models in PyTorch

C++那些事

Model interpretability and understanding for PyTorch

Attributing predictions made by the Inception network using the Integrated Gradients method

A PyTorch-based toolkit for natural language processing