IOS App: Mortar calculator for the video game Squad
-
Updated
Mar 26, 2018 - Swift
IOS App: Mortar calculator for the video game Squad
Tensorflow implementation and pre-trained models of QANet for machine reading comprehension
Implementation of a Dynamic Coattention Network to answer questions in the SQuAD question/answer dataset.
Pytorch Implenetation of Dynamic Coattention Networks +. Mixed Reinforcement learning objective(self critic) and Cross Entropy loss for supervised learning
❓✔️ BERT-based model which returns “an answer”, given a user question and a passage which includes the answer of the question
A simple python script to crawl worldfootball.net and find club and national squad mates of any footballer
A repository for Extractive Question Answering, using BERT model and SQuAD dataset.
NLU_NLG Winter Semester
squad mod
Extractive Question-Answering with BERT on SQuAD v2.0 (Stanford Question Answering Dataset) using NVIDIA PyTorch Lightning
Stanford Question Answering Dataset Translated to Indonesia.
Pipeline for performing question-answering tasks using the Stanford Question Answering Dataset (SQuAD) 2.0.
Add a description, image, and links to the squad topic page so that developers can more easily learn about it.
To associate your repository with the squad topic, visit your repo's landing page and select "manage topics."