Yuyoo
Follow
Stars
agentUniverse is a LLM multi-agent framework that allows developers to easily build multi-agent applications.
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.
Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)
🦜⛏️ Did you say you like data?
Awesome multilingual OCR and Document Parsing toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools,…
The official Python library for the OpenAI API
EMNLP 2024 Findings "Schema-Driven Information Extraction from Heterogeneous Tables"
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
A Python library to extract tabular data from PDFs
Compute benchmark of table structure recognition.
Table Transformer (TATR) is a deep learning model for extracting tables from unstructured documents (PDFs and images). This is also the official repository for the PubTables-1M dataset and GriTS ev…
Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022
[Paper] Code for the EMNLP2023 (Findings) paper "Global Structure Knowledge-Guided Relation Extraction Method for Visually-Rich Document"
A large-scale complex question answering evaluation of ChatGPT and similar large-language models
本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/
面向开发者的 LLM 入门教程，吴恩达大模型系列课程中文版
MS-Agent: Lightweight Framework for Empowering Agents with Autonomous Exploration
Pytorch implementation of Domain Separation Networks
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
Coherent Deconfounding Autoencoder (CODE-AE) can extract both common biological signals shared by incoherent samples and private representations unique to each data set, transfer knowledge learned …
《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！🚀
程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).
总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力