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PyTorch deep learning models for text processing
A toolkit for reproducible information retrieval research built on Lucene
PyTorch implementations of neural network models for keyword spotting
Simple question answering over knowledge graphs (Mohammed et al., NAACL 2018)
simple QA over knowledge graphs on DBpedia
Noise-Contrastive Estimation for Question Answering with Convolutional Neural Networks (Rao et al. CIKM 2016)
Tooling for Slack-based GPU resource management.
Anserini embedding utils
Web app for keyword spotting using TensorflowJS
Anserini integration with Solr
An in-browser visualization of Kim CNN
Keyword spotting using audio from speech synthesis services and YouTube
Data synthesized or fetched by Parrot.
Freetext question answering on Raspberry Pi (PiQA)
Neural network inference on serverless architecture
Very Deep Pairwise Word Interaction Neural Networks for modeling textual similarity (He and Lin, NAACL/HLT 2016)
Torch implementation of Severyn and Moschitti's SIGIR 2015 CNN model for question answering
Multi-Perspective Convolutional Neural Networks for modeling textual similarity (He et al., EMNLP 2015)
PyTorch utilities for parameter pruning and multiplies reduction
Hosting dataset for BuboQA
Pre-trained models for Honk
Data for Honk
Understanding the deep learning models