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38 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 24 datasets. www.pfllib.com/
搜索、推荐、广告、用增等工业界实践文章收集(来源:知乎、Datafuntalk、技术公众号)
Advanced Multi-Turn QA System with LLM and Intent Recognition. 基于LLM大语言模型意图识别、参数抽取结合slot词槽技术实现多轮问答、NL2API. 打造Function Call多轮问答最佳实践
【LLMs九层妖塔】分享 LLMs在自然语言处理(ChatGLM、Chinese-LLaMA-Alpaca、小羊驼 Vicuna、LLaMA、GPT4ALL等)、信息检索(langchain)、语言合成、语言识别、多模态等领域(Stable Diffusion、MiniGPT-4、VisualGLM-6B、Ziya-Visual等)等 实战与经验。
AIGC-interview/CV-interview/LLMs-interview面试问题与答案集合仓,同时包含工作和科研过程中的新想法、新问题、新资源与新项目
《代码随想录》LeetCode 刷题攻略:200道经典题目刷题顺序,共60w字的详细图解,视频难点剖析,50余张思维导图,支持C++,Java,Python,Go,JavaScript等多语言版本,从此算法学习不再迷茫!🔥🔥 来看看,你会发现相见恨晚!🚀
🔥LeetCode solutions in any programming language | 多种编程语言实现 LeetCode、《剑指 Offer(第 2 版)》、《程序员面试金典(第 6 版)》题解
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
为GPT/GLM等LLM大语言模型提供实用化交互接口,特别优化论文阅读/润色/写作体验,模块化设计,支持自定义快捷按钮&函数插件,支持Python和C++等项目剖析&自译解功能,PDF/LaTex论文翻译&总结功能,支持并行问询多种LLM模型,支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, m…
🕹️ A toolkit for document-level event extraction, containing some SOTA model implementations.
Natural Language Processing Tasks and References
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Source code and dataset for EMNLP 2020 paper "MAVEN: A Massive General Domain Event Detection Dataset".
A list of NLP resources focused on event extraction task
Source code for EMNLP-IJCNLP 2019 paper "Event Detection with Trigger-Aware Lattice Neural Network".
《动手学深度学习》:面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
The data and code for our IJCAI-ECAI 2018 paper: Constructing Narrative Event Evolutionary Graph for Script Event Prediction
Companion webpage to the book "Mathematics For Machine Learning"