NLP tool to extract emotional phrase from tweets 🤩

Related tags

Text Data & NLPnlpdockerextractionsentimentpytorchhuggingface
Overview

Emotional phrase extractor

Extract phrase in the given text that is used to express the sentiment. Capturing sentiment in language is important in these times where decisions and reactions are created and updated in seconds. But, which words actually lead to the sentiment description? This project aims to solve this problem.

Powered using Pytorch + hugggingface 🤗

Try it out.

git clone https://github.com/shahules786/twitter-emotions.git

cd twitter-emotions

sudo docker build --tag twitter-emotions:api .

sudo docker run -p 9999:9999  -it twitter-emotions:api python twitteremotions/app.py

Server will start running on port 9999 of localhost

Example

Installation for development

git clone https://github.com/shahules786/twitter-emotions.git

cd twitter-emotions

pip install -r requirements.txt

Train Model on your data

from twitteremotions.emotions import TwitterEmotions
emotions = TwitterEmotions()
emotions.train(train_path="data/train.csv", epochs=10, batch_size=32, max_len=168, test_size=0.25)

Contributing

All contrbutions are welcome 👋

You might also like...
HuggingTweets - Train a model to generate tweets
HuggingTweets - Train a model to generate tweets

HuggingTweets - Train a model to generate tweets Create in 5 minutes a tweet generator based on your favorite Tweeter Make my own model with the demo

Boris Dayma 318 Jan 4, 2023
Colibri core is an NLP tool as well as a C++ and Python library for working with basic linguistic constructions such as n-grams and skipgrams (i.e patterns with one or more gaps, either of fixed or dynamic size) in a quick and memory-efficient way. At the core is the tool ``colibri-patternmodeller`` whi ch allows you to build, view, manipulate and query pattern models.

Colibri Core by Maarten van Gompel, [email protected], Radboud University Nijmegen Licensed under GPLv3 (See http://www.gnu.org/licenses/gpl-3.0.html

Maarten van Gompel 122 Nov 17, 2022
Python bindings to the dutch NLP tool Frog (pos tagger, lemmatiser, NER tagger, morphological analysis, shallow parser, dependency parser)

Frog for Python This is a Python binding to the Natural Language Processing suite Frog. Frog is intended for Dutch and performs part-of-speech tagging

Maarten van Gompel 46 Dec 14, 2022
The tool to make NLP datasets ready to use
The tool to make NLP datasets ready to use

chazutsu photo from Kaikado, traditional Japanese chazutsu maker chazutsu is the dataset downloader for NLP. import chazutsu r = chazutsu.data

chakki 243 Dec 29, 2022
Snips Python library to extract meaning from text
Snips Python library to extract meaning from text

Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur

Snips 3.7k Dec 30, 2022
Search for documents in a domain through Google. The objective is to extract metadata

MetaFinder - Metadata search through Google _____ __ ___________ .__ .___ / \

Josué Encinar 85 Dec 16, 2022
Extract Keywords from sentence or Replace keywords in sentences.
Extract Keywords from sentence or Replace keywords in sentences.

FlashText This module can be used to replace keywords in sentences or extract keywords from sentences. It is based on the FlashText algorithm. Install

Vikash Singh 5.3k Jan 1, 2023
Snips Python library to extract meaning from text
Snips Python library to extract meaning from text

Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur

Snips 3.5k Feb 12, 2021
Textpipe: clean and extract metadata from text
Textpipe: clean and extract metadata from text

textpipe: clean and extract metadata from text textpipe is a Python package for converting raw text in to clean, readable text and extracting metadata

Textpipe 298 Nov 21, 2022
Comments
  • avoid confusion : end_tokens instead of start_tokens

    avoid confusion : end_tokens instead of start_tokens

    Avoid Confusion

    Replace start_tokens with end_tokens for the fourth argument to calculate the loss function to avoid confusion :)

    While reviewing your amazing project, I noticed that the EmotionData class of the dataloader.py file is returning:

    {
    ...
   # start_tokens
   "start_tokens": torch.tensor(start_tokens, dtype=torch.long),
   # end_tokens
   "end_tokens": torch.tensor(end_tokens, dtype=torch.long),
}

    But in the engine.py file you are passing start_tokens for both the third and fourth arguments of the loss_fn():

    loss = loss_fn(
            start, end, torch.argmax(data["start_tokens"], axis=1), torch.argmax(data["start_tokens"], axis=1)
        )

    But the fourth has to be end_tokens. This minor change will not affect the loss_fn() output function since they are equal in all cases [=1].But, to respect conventions and avoid confusion, it would be better if it looks like the one shown below on the right:

    image

    opened by zekaouinoureddine 0
Releases(v1.0.0)
Owner
Shahul ES
Data Scientist | Kaggle GrandMaster ( Rank 20) | Opensource @mljar
Shahul ES
GitHub Repository
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.

What is MUSE? MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (16 languages) of Universal Sentence Encoder (USE). MUS

Dani El-Ayyass 47 Sep 05, 2022
DeBERTa: Decoding-enhanced BERT with Disentangled Attention

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis

Microsoft 1.2k Jan 03, 2023
Python library for Serbian Natural language processing (NLP)

SrbAI - Python biblioteka za procesiranje srpskog jezika SrbAI je projekat prikupljanja algoritama i modela za procesiranje srpskog jezika u jedinstve

Serbian AI Society 3 Nov 22, 2022
this repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here

uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain

1 Nov 02, 2021
The official implementation of VAENAR-TTS, a VAE based non-autoregressive TTS model.

VAENAR-TTS This repo contains code accompanying the paper "VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis". Sa

THUHCSI 138 Oct 28, 2022
ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.

Antlr Project 13.6k Jan 05, 2023
Outreachy TFX custom component project

Schema Curation Custom Component Outreachy TFX custom component project This repo contains the code for Schema Curation Custom Component made as a par

Robert Crowe 5 Jul 16, 2021
Submit issues and feature requests for our API here.

AIx GPT API Submit issues and feature requests for our API here. See https://apps.aixsolutionsgroup.com for more info. Python Quick Start pip install

AIx Solutions 7 Mar 27, 2022
A simple visual front end to the Maya UE4 RBF plugin delivered with MetaHumans

poseWrangler Overview PoseWrangler is a simple UI to create and edit pose-driven relationships in Maya using the MayaUE4RBF plugin. This plugin is dis

Christopher Evans 105 Dec 18, 2022
Machine translation models released by the Gourmet project

Gourmet Models Overview The Gourmet project has released several machine translation models to translate low-resource languages. This repository conta

Edinburgh NLP 5 Dec 08, 2021
FewCLUE: 为中文NLP定制的小样本学习测评基准

FewCLUE: 为中文NLP定制的小样本学习测评基准

CLUE benchmark 387 Jan 04, 2023
Global Rhythm Style Transfer Without Text Transcriptions

Global Prosody Style Transfer Without Text Transcriptions This repository provides a PyTorch implementation of AutoPST, which enables unsupervised glo

Kaizhi Qian 193 Dec 30, 2022
Code for CVPR 2021 paper: Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A

Amazon 69 Jan 03, 2023
Rootski - Full codebase for rootski.io (without the data)

📣 Welcome to the Rootski codebase! This is the codebase for the application run

Eric 20 Nov 18, 2022
Using context-free grammar formalism to parse English sentences to determine their structure to help computer to better understand the meaning of the sentence.

Sentance Parser Executing the Program Make sure Python 3.6+ is installed. Install requirements $ pip install requirements.txt Run the program:

Vaibhaw 12 Sep 28, 2022
Twitter-NLP-Analysis - Twitter Natural Language Processing Analysis

Twitter-NLP-Analysis Business Problem I got last @turk_politika 3000 tweets with

Çağrı Karadeniz 7 Mar 12, 2022
Conditional probing: measuring usable information beyond a baseline

Conditional probing: measuring usable information beyond a baseline

John Hewitt 20 Dec 15, 2022
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS)

Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS) Yoonhyung Lee, Joongbo Shin, Kyomin Jung Abstract: Although early

LEE YOON HYUNG 147 Dec 05, 2022
translate using your voice

speech-to-text-translator Usage translate using your voice description this project makes translating a word easy, all you have to do is speak and...

1 Oct 18, 2021
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

ASAPP Research 67 Dec 01, 2022