基于“Seq2Seq+前缀树”的知识图谱问答

Last update: Dec 12, 2022

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Text Data & NLP KgCLUE-bert4keras

Overview

KgCLUE-bert4keras

基于“Seq2Seq+前缀树”的知识图谱问答

简介

博客：https://kexue.fm/archives/8802

环境

软件：bert4keras>=0.10.8
硬件：目前的结果是用一张Titan RTX（24G）跑出来的。

运行

第一次运行的时候，会给知识库构建前缀树，然后保存下来，这个过程大概需要30分钟左右；
如果是第二次运行，那么就会自动加载保存好的前缀树，这个过程大概需要5分钟左右；
保存下载的前缀树文件大概1.8G，加载到运行环境中，大概需要30G内存；
每个epoch的训练时间是很快的，反而是验证效果时间比较长，跑完训练和测试，大概需要1～2小时。

交流

QQ交流群：808623966，微信群请加机器人微信号spaces_ac_cn

Owner

苏剑林(Jianlin Su)

科学爱好者

GitHub Repository

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基于“Seq2Seq+前缀树”的知识图谱问答

Related tags

Overview

KgCLUE-bert4keras

简介

环境

运行

交流

Owner

苏剑林(Jianlin Su)

Repository to hold code for the cap-bot varient that is being presented at the SIIC Defence Hackathon 2021.

InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective

Reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer: Self-Attention with Linear Complexity)

MILES is a multilingual text simplifier inspired by LSBert - A BERT-based lexical simplification approach proposed in 2018. Unlike LSBert, MILES uses the bert-base-multilingual-uncased model, as well as simple language-agnostic approaches to complex word identification (CWI) and candidate ranking.

Question answering app is used to answer for a user given question from user given text.

CCQA A New Web-Scale Question Answering Dataset for Model Pre-Training

A Fast Command Analyser based on Dict and Pydantic

A desktop GUI providing an audio interface for GPT3.

BERTopic is a topic modeling technique that leverages 🤗 transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions

Pre-training BERT masked language models with custom vocabulary

Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Extracting Summary Knowledge Graphs from Long Documents

Based on 125GB of data leaked from Twitch, you can see their monthly revenues from 2019-2021

A python package to fine-tune transformer-based models for named entity recognition (NER).

Code for EMNLP20 paper: "ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training"

nlp基础任务

💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

Original implementation of the pooling method introduced in "Speaker embeddings by modeling channel-wise correlations"

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