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Sagnik Ray Choudhury's Projects

arxivscraper icon arxivscraper

A python module to scrape arxiv.org for a date range and category

backpack icon backpack

BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

baseline icon baseline

Strong Deep-Learning Baseline algorithms for NLP

captum icon captum

Model interpretability and understanding for PyTorch

clustype icon clustype

Automatic Entity Recognition and Typing for Massive, Domain-Specific Corpora

datasets icon datasets

🤗 The largest hub of ready-to-use NLP datasets for ML models with fast, easy-to-use and efficient data manipulation tools

description-length-probing icon description-length-probing

This is a repository with the code for the EMNLP 2020 paper "Information-Theoretic Probing with Minimum Description Length"

django-crowdsourcing icon django-crowdsourcing

Django-crowdsourcing is a highly configurable survey and report tool for journalists, with a feature set that supports a wide range of useful crowdsourcing projects.

django-crowdsourcing-1 icon django-crowdsourcing-1

Django-crowdsourcing is an MIT-licensed survey and report tool for journalists, supporting many types of survey questions and a wide variety of reporting options. A reusable Django application, it is designed to be installed easily in any Django site, including multi-site installations. Its surveys are entirely configured within the admin interface that ships with Django. While the primary focus of development is support for crowdsourcing projects, the survey tool is general purpose and can be used for a variety of applications. It is easy enough to handle simple polls with pie charts, yet powerful enough to handle complicated surveys with rich multimedia responses plotted on a map with custom icons.

duckling icon duckling

Language, engine, and tooling for expressing, testing, and evaluating composable language rules on input strings.

evalqaexpl icon evalqaexpl

Code for Evaluating Explanations for Reading Comprehension with Realistic Counterfactuals.

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