Building Question Answering System using Transformers, Pinecone and Keras
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Updated
Sep 13, 2023 - Jupyter Notebook
Building Question Answering System using Transformers, Pinecone and Keras
This is the avishkaarak-ekta-hindi model, fine-tuned using the SQuAD2.0 dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering.
ALBERT Large Model for Question and Answering System
QA app which uses Wikipedia articles to answer your questions
HealthQA_API provides a RESTful API built with FastAPI and deployed on Vercel. The API uses the sentence-transformers package with the all-MiniLM-L6-v2 model for question and answer retrieval.
Semantic Triple Assisted Learning For Question Answering Passage Re-ranking
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Multiple LLM based models for NLP tasks. Starting with Question answering on custom data
Question Answering System
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Pipeline for performing question-answering tasks using the Stanford Question Answering Dataset (SQuAD) 2.0.
This is a question answering bot that lets you find answers in research papers in Life Sciences using OpenAI's GPT-4 API.
A Chat bot that answer questions about certain topic in a given web page in 2 languages, Arabic and English
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BERT QnA API to answer prompts based on Context. (Using CDN)
This is a simple quiz project created with the help of javascript.
Constructing a corpus of ancient Chinese pediatric medicine literature, using algorithms such as BERT, lattice LSTM, and Siamese for tasks such as named entity recognition, intent recognition, entity similarity calculation, and entity linking, to develop a TCM-QA.
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