A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

MTEB: Massive Text Embedding Benchmark

Build and train state-of-the-art natural language processing models using BERT

Search with BERT vectors in Solr, Elasticsearch, OpenSearch and GSI APU

基于sentence transformers和chatglm实现的文档搜索工具

TextReducer - A Tool for Summarization and Information Extraction

Rust port of sentence-transformers (https://github.com/UKPLab/sentence-transformers)

Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity

基于sentence-transformers实现文本转向量的机器人

KoBERTopic은 BERTopic을 한국어 데이터에 적용할 수 있도록 토크나이저와 BERT를 수정한 코드입니다.

Interactive tree-maps with SBERT & Hierarchical Clustering (HAC)

Building a model to recognize incentives for landscape restoration in environmental policies from Latin America, the US and India. Bringing NLP to the world of policy analysis through an extensible framework that includes scraping, preprocessing, active learning and text analysis pipelines.

Heterogenous, Task- and Domain-Specific Benchmark for Unsupervised Sentence Embeddings used in the TSDAE paper: https://arxiv.org/abs/2104.06979.

Backend code for GitHub Recommendation Extension

Classification pipeline based on sentenceTransformer and Facebook nearest-neighbor search library

The backed for an anime recommender system that combines multiple methods to provide a variety of recommendations to users based on different similarity metrics

Match celebrity users with their respective tweets by making use of Semantic Textual Similarity on over 900+ celebrity users' 2.5 million+ scraped tweets utilizing SBERT, streamlit, tweepy and FastAPI

Package to calculate the similarity score between two sentences

A semantic food search web application built with Django, Solr, SBERT, Docker and Heroku

Плагин для SmartApp Framework, осуществляющий векторизацию (получение embedding'ов) текстов с помощью различных моделей