RaceBERT -- A transformer based model to predict race and ethnicty from names

Related tags

Deep LearningraceBERT
Overview

RaceBERT -- A transformer based model to predict race and ethnicty from names

Installation

pip install racebert

Using a virtual environment is highly recommended! You may need to install pytorch as instructed here: https://pytorch.org/get-started/locally/

Paper

Todo

Usage

raceBERT predicts race (U.S census race) and ethnicity from names.

from racebert import RaceBERT

model = RaceBERT()

# To predict race
model.predict_race("Barack Obama")
>>> {"label": "nh_black", "score": 0.5196923613548279}

The race categories are:

Race Label
Non-hispanic White nh_white
Hispanic hispanic
Non-hispanic Black nh_black
Asian & Pacific Islander api
American Indian & Alaskan Native aian
# Predict ethnicity
model.predict_ethnicty("Arjun Gupta")
>>> {"label": "Asian,IndianSubContinent", "score": 0.9612812399864197}

The ethnicity categories are:

Ethnicity
GreaterEuropean,British
GreaterEuropean,WestEuropean,French
GreaterEuropean,WestEuropean,Italian
GreaterEuropean,WestEuropean,Hispanic
GreaterEuropean,Jewish
GreaterEuropean,EastEuropean
Asian,IndianSubContinent
Asian,GreaterEastAsian,Japanese
GreaterAfrican,Muslim
Asian,GreaterEastAsian,EastAsian
GreaterEuropean,WestEuropean,Nordic
GreaterEuropean,WestEuropean,Germanic
GreaterAfrican,Africans

GPU

If you have a GPU, you can speed up the computation by specifying the CUDA device when you instantiate the model.

from racebert import RaceBERT

model = RaceBERT(device=0)

# predict race in batch
model.predict_race(["Barack Obama", "George Bush"])
>>>
[
        {"label": "nh_black", "score": 0.5196923613548279},
        {"label": "nh_white", "score": 0.8365859389305115}
]
# predict ethnicity in batch
model.predict_ethnicity(["Barack Obama", "George Bush"])

HuggingFace

Alternatively, you can work with the transformers models hosted on the huggingface hub directly.

Please refer to the transformers documentation.

Owner
Prasanna Parasurama
Prasanna Parasurama
Official Implementation of CVPR 2022 paper: "Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning"

(CVPR 2022) Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning ArXiv This repo contains Official Implementat

Yujun Shi 24 Nov 01, 2022
Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"

On-the-Fly Adaptation Official Pytorch Code base for On-the-Fly Test-time Adaptation for Medical Image Segmentation Paper Introduction One major probl

Jeya Maria Jose 17 Nov 10, 2022
A Python 3 package for state-of-the-art statistical dimension reduction methods

direpack: a Python 3 library for state-of-the-art statistical dimension reduction techniques This package delivers a scikit-learn compatible Python 3

Sven Serneels 32 Dec 14, 2022
MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

Octave Convolution MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Imag

Meta Research 549 Dec 28, 2022
SymPy-powered, Wolfram|Alpha-like answer engine totally in your browser, without backend computation

SymPy Beta SymPy Beta is a fork of SymPy Gamma. The purpose of this project is to run a SymPy-powered, Wolfram|Alpha-like answer engine totally in you

Liumeo 25 Dec 21, 2022
PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation.

PyTorch implementation of Progressive Growing of GANs for Improved Quality, Stability, and Variation. Warning: the master branch might collapse. To ob

559 Dec 14, 2022
Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication"

NFFT4ANOVA Source code for our Paper "Learning in High-Dimensional Feature Spaces Using ANOVA-Based Matrix-Vector Multiplication" This package uses th

Theresa Wagner 1 Aug 10, 2022
This is an official implementation for "PlaneRecNet".

PlaneRecNet This is an official implementation for PlaneRecNet: A multi-task convolutional neural network provides instance segmentation for piece-wis

yaxu 50 Nov 17, 2022
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation (CVPR 2021)

Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Input Image Initial CAM Successive Maps with adversar

Jungbeom Lee 110 Dec 07, 2022
Mixed Neural Likelihood Estimation for models of decision-making

Mixed neural likelihood estimation for models of decision-making Mixed neural likelihood estimation (MNLE) enables Bayesian parameter inference for mo

mackelab 9 Dec 22, 2022
Real-time 3D multi-person detection made easy with OpenPose and the ZED

OpenPose ZED This sample show how to simply use the ZED with OpenPose, the deep learning framework that detects the skeleton from a single 2D image. T

blanktec 5 Nov 06, 2020
Code for SALT: Stackelberg Adversarial Regularization, EMNLP 2021.

SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R

Simiao Zuo 10 Jan 10, 2022
deep_image_prior_extension

Code for "Is Deep Image Prior in Need of a Good Education?" Project page: https://jleuschn.github.io/docs.educated_deep_image_prior/. Supplementary Ma

riccardo barbano 7 Jan 09, 2022
đŸ€— Push your spaCy pipelines to the Hugging Face Hub

spacy-huggingface-hub: Push your spaCy pipelines to the Hugging Face Hub This package provides a CLI command for uploading any trained spaCy pipeline

Explosion 30 Oct 09, 2022
Controlling the MicriSpotAI robot from scratch

Project-MicroSpot-AI Controlling the MicriSpotAI robot from scratch Colaborators Alexander Dennis Components from MicroSpot The MicriSpotAI has the fo

Dennis NĂșñez-FernĂĄndez 5 Oct 20, 2022
ROMP: Monocular, One-stage, Regression of Multiple 3D People, ICCV21

Monocular, One-stage, Regression of Multiple 3D People ROMP, accepted by ICCV 2021, is a concise one-stage network for multi-person 3D mesh recovery f

Yu Sun 937 Jan 04, 2023
A Deep Reinforcement Learning Framework for Stock Market Trading

DQN-Trading This is a framework based on deep reinforcement learning for stock market trading. This project is the implementation code for the two pap

61 Jan 01, 2023
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection

DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection Code for our Paper DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Obje

Steven Lang 58 Dec 19, 2022
Tracking code for the winner of track 1 in the MMP-Tracking Challenge at ICCV 2021 Workshop.

Tracking Code for the winner of track1 in MMP-Trakcing challenge This repository contains our tracking code for the Multi-camera Multiple People Track

DamoCV 29 Nov 13, 2022
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals

Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of

Juan Haladjian 114 Nov 27, 2022