2021搜狐校园文本匹配算法大赛baseline
分享了一个搜狐文本匹配的baseline，主要是通过条件LayerNorm来增加模型的多样性，以实现同一模型处理不同类型的数据、形成不同输出的目的。
线下验证集F1约0.74，线上测试集F1约0.73。预训练模型是RoFormer，也欢迎对比其他预训练模型的效果。
测试环境：tensorflow 1.14 + keras 2.3.1 + bert4keras 0.10.5，如果在其他环境组合下报错，请根据错误信息自行调整代码。
详情请看：https://kexue.fm/archives/8337
QQ交流群：808623966，微信群请加机器人微信号spaces_ac_cn
CIRPLANT This repository contains the code and pre-trained models for Composed Image Retrieval using Pretrained LANguage Transformers (CIRPLANT) For d
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
jel: Japanese Entity Linker jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese. Usage Currently, link and question methods
WIT (Wikipedia-based Image Text) Dataset is a large multimodal multilingual dataset comprising 37M+ image-text sets with 11M+ unique images across 100+ languages.
Open-Domain Question Answering(ODQA)는 다양한 주제에 대한 문서 집합으로부터 자연어 질의에 대한 답변을 찾아오는 task입니다. 이때 사용자 질의에 답변하기 위해 주어지는 지문이 따로 존재하지 않습니다. 따라서 사전에 구축되어있는 Knowl
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation This is the official PyTorch implementation
A repo for open resources & information for people to succeed in PhD in CS & career in AI / NLP
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
jellyfish Jellyfish is a python library for doing approximate and phonetic matching of strings. Written by James Turk
smaller-LaBSE LaBSE(Language-agnostic BERT Sentence Embedding) is a very good method to get sentence embeddings across languages. But it is hard to fi
baller2vec++ This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec++: A Look-Ahead Multi-Entity Transformer For Modeling
keytotext Idea is to build a model which will take keywords as inputs and generate sentences as outputs. Potential use case can include: Marketing Sea
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page
BPEer Train BPE with fastBPE, and load to Huggingface Tokenizer. Description The BPETrainer of Huggingface consumes a lot of memory when I am training
CoNLL-English NER Task en | ch Motivation Course Project review the pytorch framework and sequence-labeling task practice using the transformers of Hu
Two-Stage Text Summarization Description We experiment with a 2-stage summarization model on CNN/DailyMail dataset that combines the ability to filter
VADER-Sentiment-Analysis VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifica
Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1
Cải thiện Elasticsearch trong bài toán semantic search sử dụng phương pháp Sentence Embeddings Trong bài viết này mình sẽ sử dụng pretrain model SimCS
🤗 🖼️ HuggingPics Fine-tune Vision Transformers for anything using images found on the web. Check out the video below for a walkthrough of this proje
29 Nov 17, 2022
514 Nov 17, 2022
10 Jan 06, 2023
740 Dec 24, 2022
69 Nov 04, 2022
564 Jan 08, 2023
420 Dec 28, 2022
1.6k Dec 27, 2022
13 Sep 02, 2022
30 Dec 16, 2022
364 Jan 03, 2023
1.4k Dec 29, 2022
1 Dec 23, 2021
2 Jan 14, 2022
6 Oct 22, 2022
3.8k Dec 30, 2022
169 Dec 21, 2022
18 Nov 25, 2022
185 Dec 21, 2022