rohitgandikota/bert-qa
This project shows the usage of hugging face framework to answer questions using a deep learning model for NLP called BERT. This work can be adopted and used in many application in NLP like smart assistant or chat-bot or smart information center.
This tool helps you quickly find specific answers to questions within long documents or pieces of text. You provide a question and either a PDF file or plain text, and it returns the most relevant answer directly from the content. It's ideal for anyone who needs to extract precise information from reports, articles, or other textual data without manually sifting through it.
No commits in the last 6 months.
Use this if you frequently need to pinpoint exact answers to questions buried within large documents or extensive text passages.
Not ideal if you need to summarize entire documents or engage in a free-form conversation, as it's designed for direct question-answering from provided context.
Stars
11
Forks
2
Language
Python
License
—
Category
Last pushed
Jun 21, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/rohitgandikota/bert-qa"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
5hirish/adam_qas
ADAM - A Question Answering System. Inspired from IBM Watson
husseinmozannar/SOQAL
Arabic Open Domain Question Answering System using Neural Reading Comprehension
SatyamSoni23/Smart-Question-Answering-System-on-Document
It's Smart-Question Answering System on short as well as long documents. It can automatically...
dharmendrach/bert_quora_question_pairs
BERT Model Fine-tuning on Quora Questions Pairs
nlpunibo/Question-Answering-SQUAD
Question Answering model based on DistilBERT, trained and evaluated on the SQUAD dataset