SBERT-WK-Sentence-Embedding

Sentence embedder

A method to generate sentence embeddings from pre-trained language models

IEEE/ACM TASLP 2020: SBERT-WK: A Sentence Embedding Method By Dissecting BERT-based Word Models

GitHub

178 stars
7 watching
25 forks
Language: Python
last commit: over 5 years ago

Related projects:

RepositoryDescriptionStars
jwieting/acl2017A codebase for training and using models of sentence embeddings.33
iarroyof/sentence_embeddingA method to convert word embeddings into sentence representations by applying entropy weights calculated from TFIDF transform.9
oborchers/fast_sentence_embeddingsA Python library for efficiently computing sentence embeddings from large datasets618
lajanugen/s2vAn implementation of a neural network model for learning efficient sentence representations from text data.205
jwieting/para-nmt-50mA collection of pre-trained models and code for training paraphrastic sentence embeddings from large machine translation datasets.102
bohanli/bert-flowAn implementation of a method to generate sentence embeddings from pre-trained language models using TensorFlow.530
princetonml/sifA Python implementation of a sentence embedding algorithm using the Smooth Inverse Frequency weighting scheme1,084
nlprinceton/text_embeddingA utility class for generating and evaluating document representations using word embeddings.54
kudkudak/word-embeddings-benchmarksProvides methods for evaluating word embeddings on various benchmarks437
jwieting/charagramA tool for training and using character n-gram based word and sentence embeddings in natural language processing.125
epfml/sent2vecAn unsupervised technique to generate numerical representations of sentences and words for use in machine learning tasks1,194
xiaoqijiao/coling2018Provides training and testing code for a CNN-based sentence embedding model2
kostyaev/sentence2vecThis is a tool for creating deep sentence embeddings using Sequence-to-Sequence learning.22
voidism/diffcseAn unsupervised contrastive learning framework for learning sentence embeddings sensitive to differences between original and edited sentences.292
fursovia/geometric_embeddingAn implementation of a non-parameterized approach for building sentence representations19