Code for the paper "A Simple but Tough-to-Beat Baseline for Sentence Embeddings".

Related tags

Text Data & NLPSIF
Overview

SIF

This is the code for the paper "A Simple but Tough-to-Beat Baseline for Sentence Embeddings".

The code is written in python and requires numpy, scipy, pickle, sklearn, theano and the lasagne library. Some functions/classes are based on the code of John Wieting for the paper "Towards Universal Paraphrastic Sentence Embeddings" (Thanks John!). The example data sets are also preprocessed using the code there.

Install

To install all dependencies virtualenv is suggested:

$ virtualenv .env
$ . .env/bin/activate
$ pip install -r requirements.txt 

Get started

To get started, cd into the directory examples/ and run demo.sh. It downloads the pretrained GloVe word embeddings, and then runs the scripts:

  • sif_embedding.py is an demo on how to generate sentence embedding using the SIF weighting scheme,
  • sim_sif.py and sim_tfidf.py are for the textual similarity tasks in the paper,
  • supervised_sif_proj.sh is for the supervised tasks in the paper.

Check these files to see the options.

Source code

The code is separated into the following parts:

  • SIF embedding: involves SIF_embedding.py. The SIF weighting scheme is very simple and is implmented in a few lines.
  • textual similarity tasks: involves data_io.py, eval.py, and sim_algo.py. data_io provides the code for reading the data, eval is for evaluating the performance, and sim_algo provides the code for our sentence embedding algorithm.
  • supervised tasks: involves data_io.py, eval.py, train.py, proj_model_sim.py, and proj_model_sentiment.py. train provides the entry for training the models (proj_model_sim is for the similarity and entailment tasks, and proj_model_sentiment is for the sentiment task). Check train.py to see the options.
  • utilities: includes lasagne_average_layer.py, params.py, and tree.py. These provides utility functions/classes for the above two parts.

References

For technical details and full experimental results, see the paper.

@article{arora2017asimple, 
	author = {Sanjeev Arora and Yingyu Liang and Tengyu Ma}, 
	title = {A Simple but Tough-to-Beat Baseline for Sentence Embeddings}, 
	booktitle = {International Conference on Learning Representations},
	year = {2017}
}
Retraining OpenAI's GPT-2 on Discord Chats

Train OpenAI's GPT-2 on Discord Chats Retraining a Text Generation Model on Discord Chats using gpt-2-simple that wraps existing model fine-tuning and

Ayush Mishra 4 Oct 27, 2022
Contains descriptions and code of the mini-projects developed in various programming languages

TexttoSpeechAndLanguageTranslator-project introduction A pleasant application where the client will be given buttons like play,reset and exit. The cli

Adarsh Reddy 1 Dec 22, 2021
Search-Engine - 📖 AI based search engine

Search Engine AI based search engine that was trained on 25000 samples, feel free to train on up to 1.2M sample from kaggle dataset, link below StackS

Vladislav Kruglikov 2 Nov 29, 2022
Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models

PEGASUS library Pre-training with Extracted Gap-sentences for Abstractive SUmmarization Sequence-to-sequence models, or PEGASUS, uses self-supervised

Google Research 1.4k Dec 22, 2022
Python code for ICLR 2022 spotlight paper EViT: Expediting Vision Transformers via Token Reorganizations

Expediting Vision Transformers via Token Reorganizations This repository contain

Youwei Liang 101 Dec 26, 2022
Espial is an engine for automated organization and discovery of personal knowledge

Live Demo (currently not running, on it) Espial is an engine for automated organization and discovery in knowledge bases. It can be adapted to run wit

Uzay-G 159 Dec 30, 2022
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.

anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam

Hiroki Nakayama 1.5k Dec 05, 2022
A number of methods in order to perform Natural Language Processing on live data derived from Twitter

A number of methods in order to perform Natural Language Processing on live data derived from Twitter

1 Nov 24, 2021
Download videos from YouTube/Twitch/Twitter right in the Windows Explorer, without installing any shady shareware apps

youtube-dl and ffmpeg Windows Explorer Integration Download videos from YouTube/Twitch/Twitter and more (any platform that is supported by youtube-dl)

Wolfgang 226 Dec 30, 2022
Materials (slides, code, assignments) for the NYU class I teach on NLP and ML Systems (Master of Engineering).

FREE_7773 Repo containing material for the NYU class (Master of Engineering) I teach on NLP, ML Sys etc. For context on what the class is trying to ac

Jacopo Tagliabue 90 Dec 19, 2022
Unsupervised Language Model Pre-training for French

FlauBERT and FLUE FlauBERT is a French BERT trained on a very large and heterogeneous French corpus. Models of different sizes are trained using the n

GETALP 212 Dec 10, 2022
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2

Google Research Datasets 52 Jun 21, 2022
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants

Rasa Open Source Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual

Rasa 15.3k Dec 30, 2022
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern Pattern is a web mining module for Python. It has tools for: Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM par

Computational Linguistics Research Group 8.4k Dec 30, 2022
A Plover python dictionary allowing for consistent symbol input with specification of attachment and capitalisation in one stroke.

Emily's Symbol Dictionary Design This dictionary was created with the following goals in mind: Have a consistent method to type (pretty much) every sy

Emily 68 Jan 07, 2023
中文空间语义理解评测

中文空间语义理解评测 最新消息 2021-04-10 🚩 排行榜发布: Leaderboard 2021-04-05 基线系统发布: SpaCE2021-Baseline 2021-04-05 开放数据提交: 提交结果 2021-04-01 开放报名: 我要报名 2021-04-01 数据集 pa

40 Jan 04, 2023
The NewSHead dataset is a multi-doc headline dataset used in NHNet for training a headline summarization model.

This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.

Google Research Datasets 31 Jul 15, 2022
Grading tools for Advanced NLP (11-711)Grading tools for Advanced NLP (11-711)

Grading tools for Advanced NLP (11-711) Installation You'll need docker and unzip to use this repo. For docker, visit the official guide to get starte

Hao Zhu 2 Sep 27, 2022
Reformer, the efficient Transformer, in Pytorch

Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH

Phil Wang 1.8k Dec 30, 2022