In this we generate QA pairs from the paragraph content and pdf content
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Updated
Sep 18, 2024 - Jupyter Notebook
In this we generate QA pairs from the paragraph content and pdf content
In this Project We perform NLP tasks like QA Pair Generation, Question Answering, Text Summarization and Data Extraction from webpages using Large Language Models (Like Gemini ) and Langchain
Text2Text: Crosslingual NLP/G toolkit
Multilingual/multidomain question generation datasets, models, and python library for question generation.
InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
Mimix: A Text Generation Tool and Pretrained Chinese Models
AI powered API for generating personalised study questions. All you have to do is to pass in your course material as a PDF file, and then question would be generated based on its content
EQGG: Automatic Question Group Generation
A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
TreeInstruct is a novel method that uses state space estimation and dynamic tree-based questioning for multi-turn Socratic instruction, applied to code debugging.
this is a repository for question and answer generation (QAG). here we train answer extraction (AE) and question generation (QG) models. models with soon be publicly available at pbe.achybl.com
a tool to generate questions and answers from pdf files
This is a smart Quiz Generator that generates a dynamic quiz from any uploaded text/PDF document using NLP. This can be used for self-analysis, question paper generation, and evaluation, thus reducing human effort.
A study on Knowledge-based question generation from images. Undergraduate Thesis for 2023-2024.
Question-Answer Generation Control for English, using the T5 model and Pytorch lightning. Training, inference and evaluation scripts included.
Code for paper "FairytaleQA Translated: Enabling Educational Question and Answer Generation in Less-Resourced Languages"
Implementation for Conditional Text GANs and Analysis with Integrated Gradients
Indonesian Question Answering and Question Generation using Transformers
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