PersianQAPersian (Farsi) Question Answering Dataset (+ Models)
Stars: ✭ 114 (+111.11%)
Mutual labels: question-answering, squad, reading-comprehension
extractive rc by runtime mtCode and datasets of "Multilingual Extractive Reading Comprehension by Runtime Machine Translation"
Stars: ✭ 36 (-33.33%)
Mutual labels: question-answering, squad, reading-comprehension
qaTensorFlow Models for the Stanford Question Answering Dataset
Stars: ✭ 72 (+33.33%)
Mutual labels: question-answering, squad
cmrc2019A Sentence Cloze Dataset for Chinese Machine Reading Comprehension (CMRC 2019)
Stars: ✭ 118 (+118.52%)
Mutual labels: question-answering, reading-comprehension
explicit memory tracker[ACL 2020] Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading
Stars: ✭ 35 (-35.19%)
Mutual labels: question-answering, reading-comprehension
Pytorch Question AnsweringImportant paper implementations for Question Answering using PyTorch
Stars: ✭ 154 (+185.19%)
Mutual labels: question-answering, attention-mechanism
cmrc2017The First Evaluation Workshop on Chinese Machine Reading Comprehension (CMRC 2017)
Stars: ✭ 90 (+66.67%)
Mutual labels: question-answering, reading-comprehension
cdQA-ui⛔ [NOT MAINTAINED] A web interface for cdQA and other question answering systems.
Stars: ✭ 19 (-64.81%)
Mutual labels: question-answering, reading-comprehension
TOEFL-QAA question answering dataset for machine comprehension of spoken content
Stars: ✭ 61 (+12.96%)
Mutual labels: question-answering, reading-comprehension
ODSQAODSQA: OPEN-DOMAIN SPOKEN QUESTION ANSWERING DATASET
Stars: ✭ 43 (-20.37%)
Mutual labels: question-answering, reading-comprehension
question-answeringNo description or website provided.
Stars: ✭ 32 (-40.74%)
Mutual labels: question-answering, squad
Haystack🔍 Haystack is an open source NLP framework that leverages Transformer models. It enables developers to implement production-ready neural search, question answering, semantic document search and summarization for a wide range of applications.
Stars: ✭ 3,409 (+6212.96%)
Mutual labels: question-answering, squad
Bi Att FlowBi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.
Stars: ✭ 1,472 (+2625.93%)
Mutual labels: question-answering, squad
CompareModels TRECQACompare six baseline deep learning models on TrecQA
Stars: ✭ 61 (+12.96%)
Mutual labels: question-answering, attention-mechanism
Awesome Qa😎 A curated list of the Question Answering (QA)
Stars: ✭ 596 (+1003.7%)
Mutual labels: question-answering, squad
exams-qaA Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering
Stars: ✭ 25 (-53.7%)
Mutual labels: question-answering, reading-comprehension
SQUAD2.Q-Augmented-DatasetAugmented version of SQUAD 2.0 for Questions
Stars: ✭ 31 (-42.59%)
Mutual labels: question-answering, squad
Medi-CoQAConversational Question Answering on Clinical Text
Stars: ✭ 22 (-59.26%)
Mutual labels: question-answering, squad
cherche📑 Neural Search
Stars: ✭ 196 (+262.96%)
Mutual labels: question-answering