STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums.

Last update: Nov 05, 2021

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Overview

stsb_multi_mt_en

STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums. (source)

How to use this model from the sentence transformers library:

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("abhijithneilabraham/stsb_multi_mt_distilbert-base-uncased")

Find the evaluation results here

Owner

Abhijith Neil Abraham

AI Research Engineer| NLP|Deep Learning

GitHub Repository

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STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums.

Related tags

Overview

stsb_multi_mt_en

Owner

Abhijith Neil Abraham

Python library for Serbian Natural language processing (NLP)

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STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums.

Related tags

Overview

stsb_multi_mt_en

Owner

Abhijith Neil Abraham

Python library for Serbian Natural language processing (NLP)

A programming language with logic of Python, and syntax of all languages.

An easy-to-use Python module that helps you to extract the BERT embeddings for a large text dataset (Bengali/English) efficiently.

SHAS: Approaching optimal Segmentation for End-to-End Speech Translation

Calibre recipe to convert latest issue of Analyse & Kritik into an ebook

Submit issues and feature requests for our API here.

CYGNUS, the Cynical AI, combines snarky responses with uncanny aggression.

A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

Lightweight utility tools for the detection of multiple spellings, meanings, and language-specific terminology in British and American English

Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

keras implement of transformers for humans

COVID-19 Related NLP Papers

Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Semantic Segmentation".

Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.

Suite of 500 procedurally-generated NLP tasks to study language model adaptability

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