sbert

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

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

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

using machine learning on anki collection for: enhanced scheduling, semantic plotting, semantic clustering, searching by semantic similarity

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

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

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

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

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

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

Projects for the Artificial Intelligence 2 course at the University of Athens.

Some Python scripts and Java classes to make several open source toolkits to work with CLEF (PubMed docs) and TREC Common Core datasets. The code developed aimed to improve document classification by exploring some pretrained word embeddings like BERT and PubMedBERT and to investigate a Semantic search approach incorporating the Sentence-BERT model for both datasets.

⚕️🦠 Developed a document retrieval system to return titles of scientific papers containing the answer to a given user question based on the first version of the COVID-19 Open Research Dataset (CORD-19) ☣️🧬

Datasets and models for medical concept normalization (MCN) in English and German. Results of Bachelor Thesis about MCN using BERT / SBERT.

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

This project is about developing a document retrieval system to return titles of scientific papers containing the answer to a given user question. Two different sentence embedding approaches have been implemented and compared.

Linux manual search shell with natural language

Usage of BERT models for text clustering techniques using sentence embeddings

Scripts e utilitários para modelagem e identificação de tópicos relativos a depressão no Reddit, em língua portuguesa e inglesa, usando técnicas de modelagem de tópicos. Os modelos de tópicos Latent Dirichlet Allocation (LDA), Contextualized Topic Model (CTM) e Embedded Topic Model (ETM) foram explorados neste estudo.

In this project, I use sentence embeddings to identify question pairs

Built a news topic classification model using pre trained sentence BERT model and traditional ML models. Sentence bert is used to generate sentence embedding and sbert embedding are used to train various ML models.Achieved an accuracy of 94.3% using SVM and Sbert model.

Evaluation of Summarization Tasks using Sentence Bert

A semantic search engine prototype, made with SentenceBERT, ontological definitions, and full-text search.

Project files contain PyTorch implementations for Siamese BiLSTM models for Semantic Text Similarity task on the SICK Dataset using FastText embeddings. Also contains Siamese BiLSTM-Transformer Encoder and SBERT fine-tuning implementations on the STS Data tasks.

Sentence Bert for Question-Answering on COVID-19 Open Research Dataset (CORD-19)

patent-sberta training with triplet data

Initially implement Document-Retrieval-System with SBERT embeddings and evaluate it in CORD-19 dataset. Afterwards, fine tune BERT model with SQuAD.v2 dataset so as to evaluate it in Question Answering task.