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计算机专业课（408）思维导图和笔记：计算机组成原理（第五版 王爱英），数据结构（王道），计算机网络（第七版 谢希仁），操作系统（第四版 汤小丹）
博客配套视频链接: https://space.bilibili.com/383551518?spm_id_from=333.1007.0.0 b 站直接看 配套 github 链接：https://github.com/nickchen121/Pre-training-language-model 配套博客链接：https://www.cnblogs.com/nickchen121/p/1…
近二十年公务员考试（公考）行政能力测试（行测）真题，包含国考、省考、选调生考试所有行测试卷及其答案
基于LLAMA2的增量预训练藏文大语言模型Tibetan-LLAMA2-7B&Tibetan-LLAMA2-13B；指令微调藏文大模型Tibetan-Alpaca-7B&Tibetan-Alpaca-13B。
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…
基于LLaMA2-7B增量预训练的藏文大语言模型TiLamb（Tibetan Large Language Model Base）
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…
基于TensorFlow，seq2seq+attention+beamsearch的文本摘要。
Tensorflow seq2seq Implementation of Text Summarization.
Extractive text summarization using seq2seq, PGN and coverage machanism.
GSum: A General Framework for Guided Neural Abstractive Summarization
Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality, ACL 2023
Corr F/A evaluation metrics in paper "Xinnuo Xu, Ondrej Dusek, Jingyi Li, Yannis Konstas, and Verena Rieser. Fact-based Content Weighting for Evaluating Abstractive Summarisation" Proceedings of AC…
Resources for the "Evaluating the Factual Consistency of Abstractive Text Summarization" paper
A large collection of papers related to Summarization from ten top conferences (ACL, EMNLP, NAACL, COLING, AAAI, IJCAI, NIPS, ICML, ICLR, KDD) spanning the years 2010 to 2023.
Code for the paper "Probing Bilingual Guidance for Cross-Lingual Summarization" (NLPCC 2023)
A Multi-Stage Fine-tuning-based Method for Low-resource Cross-lingual Summarization
Official code repo for paper: ACROSS: An Alignment-based Framework for Low-Resource Many-to-One Cross-Lingual Summarization
Datasets for EMNLP-IJCNLP 2019 paper "NCLS:Neural Cross-Lingual Summarization"