covid question answering datasets and fine tuned models

Related tags

Deep LearningCovid-QA
Overview

Covid-QA

Fine tuned models for question answering on Covid-19 data.

Hosted Inference

This model has been contributed to huggingface.Click here to see the model in action!

Dependencies

pip install -r requirements.txt

Getting Started

cd longformer_qa

Dataset

Covid 19 QA data obtained from transformers: covid QA deepset.
Data Generation script: generate_data.py

Inference

Longformer model fine tuned on the data: download.
download and unzip inside longformer_qa/.
Scripts on longformer_inference.py

from longformer_inference import qa
print(qa(question,context))

Example

 print(qa("What is the main cause of HIV-1 infection in children?","Functional Genetic Variants in DC-SIGNR Are Associated with Mother-to-Child Transmission of HIV-1\n\nhttps:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC2752805\/\n\nBoily-Larouche, Genevi\u00e8ve; Iscache, Anne-Laure; Zijenah, Lynn S.; Humphrey, Jean H.; Mouland, Andrew J.; Ward, Brian J.; Roger, Michel\n2009-10-07\nDOI:10.1371\/journal.pone.0007211\nLicense:cc-by\n\nAbstract: BACKGROUND: Mother-to-child transmission (MTCT) is the main cause of HIV-1 infection in children worldwide. Given that the C-type lectin receptor, dendritic cell-specific ICAM-grabbing non-integrin-related (DC-SIGNR, also known as CD209L or liver\/lymph node\u2013specific ICAM-grabbing non-integrin (L-SIGN)), can interact with pathogens including HIV-1 and is expressed at the maternal-fetal interface, we hypothesized that it could influence MTCT of HIV-1. METHODS AND FINDINGS: To investigate the potential role of DC-SIGNR in MTCT of HIV-1, we carried out a genetic association study of DC-SIGNR in a well-characterized cohort of 197 HIV-infected mothers and their infants recruited in Harare, Zimbabwe. Infants harbouring two copies of DC-SIGNR H1 and\/or H3 haplotypes (H1-H1, H1-H3, H3-H3) had a 3.6-fold increased risk of in utero (IU) (P = 0.013) HIV-1 infection and a 5.7-fold increased risk of intrapartum (IP) (P = 0.025) HIV-1"))
 
 >>>Mother-to-child transmission (MTCT)

Fine Tuning

Fine tuning script on longformer_finetune.py

Evaluation

Run evaluator.py to evaluate F1/EM scores. Current Scores : F1:62.3 | EM:37.83

Owner
Abhijith Neil Abraham
AI Research Engineer
Abhijith Neil Abraham
Repository for RNNs using TensorFlow and Keras - LSTM and GRU Implementation from Scratch - Simple Classification and Regression Problem using RNNs

RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for

Nahid Ebrahimian 13 Dec 13, 2022
A curated list of references for MLOps

A curated list of references for MLOps

Larysa Visengeriyeva 9.3k Jan 07, 2023
Sandbox for training deep learning networks

Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (

Oleg Sémery 2.7k Jan 01, 2023
[LREC] MMChat: Multi-Modal Chat Dataset on Social Media

MMChat This repo contains the code and data for the LREC2022 paper MMChat: Multi-Modal Chat Dataset on Social Media. Dataset MMChat is a large-scale d

Silver 47 Jan 03, 2023
Official Pytorch implementation of C3-GAN

Official pytorch implemenation of C3-GAN Contrastive Fine-grained Class Clustering via Generative Adversarial Networks [Paper] Authors: Yunji Kim, Jun

NAVER AI 114 Dec 02, 2022
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

Alex Gorodnitskiy 11 Mar 20, 2022
Spectrum Surveying: Active Radio Map Estimation with Autonomous UAVs

Spectrum Surveying: The Python code in this repository implements the simulations and plots the figures described in the paper “Spectrum Surveying: Ac

Universitetet i Agder 2 Dec 06, 2022
A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

ViTGAN: Training GANs with Vision Transformers A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers. Refer

Hong-Jia Chen 127 Dec 23, 2022
Multi-Person Extreme Motion Prediction

Multi-Person Extreme Motion Prediction Implementation for paper Wen Guo, Xiaoyu Bie, Xavier Alameda-Pineda, Francesc Moreno-Noguer, Multi-Person Extre

GUO-W 38 Nov 15, 2022
Kaggle competition: Springleaf Marketing Response

PruebaEnel Prueba Kaggle-Springleaf-master Prueba Kaggle-Springleaf Kaggle competition: Springleaf Marketing Response Competencia de Kaggle: Marketing

1 Feb 09, 2022
An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx

JiaKui Hu 10 Oct 28, 2022
Project repo for Learning Category-Specific Mesh Reconstruction from Image Collections

Learning Category-Specific Mesh Reconstruction from Image Collections Angjoo Kanazawa*, Shubham Tulsiani*, Alexei A. Efros, Jitendra Malik University

438 Dec 22, 2022
Code to produce syntactic representations that can be used to study syntax processing in the human brain

Can fMRI reveal the representation of syntactic structure in the brain? The code base for our paper on understanding syntactic representations in the

Aniketh Janardhan Reddy 4 Dec 18, 2022
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)

Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati

Emirhan BULUT 28 Dec 04, 2021
Kernel Point Convolutions

Created by Hugues THOMAS Introduction Update 27/04/2020: New PyTorch implementation available. With SemanticKitti, and Windows supported. This reposit

Hugues THOMAS 584 Jan 07, 2023
Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).

Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma This repo provi

Jingtao Zhan 99 Dec 27, 2022
UpChecker is a simple opensource project to host it fast on your server and check is server up, view statistic, get messages if it is down. UpChecker - just run file and use project easy

UpChecker UpChecker is a simple opensource project to host it fast on your server and check is server up, view statistic, get messages if it is down.

Yan 4 Apr 07, 2022
Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous Event-Based Data"

A Differentiable Recurrent Surface for Asynchronous Event-Based Data Code for the ECCV2020 paper "A Differentiable Recurrent Surface for Asynchronous

Marco Cannici 21 Oct 05, 2022
Binary Passage Retriever (BPR) - an efficient passage retriever for open-domain question answering

BPR Binary Passage Retriever (BPR) is an efficient neural retrieval model for open-domain question answering. BPR integrates a learning-to-hash techni

Studio Ousia 147 Dec 07, 2022
[CVPR 2021] Generative Hierarchical Features from Synthesizing Images

[CVPR 2021] Generative Hierarchical Features from Synthesizing Images

GenForce: May Generative Force Be with You 148 Dec 09, 2022