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GitHub topics: newsqa

ambideXtrous9/MTP-News-Article-based-Question-Answering-System

MTP-FlanT5-SBERT-Model-for-NewsQA-and-Teacher-Student-Model

Language: Jupyter Notebook - Size: 3.77 MB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

giannhskp/Artificial-Intelligence-II_Natural-Language-Processing

Sentiment Classifier using: Softmax-Regression, Feed-Forward Neural Network, Bidirectional stacked LSTM/GRU Recursive Neural Network, fine-tuning on BERT pre-trained model. Question Answering using BERT pre-trained model and fine-tuning it on various datasets (SQuAD, TriviaQA, NewsQ, Natural Questions, QuAC)

Language: Jupyter Notebook - Size: 6.81 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

Sitaras/BERT-Question-Answering

Question Answering using BERT pre-trained model and fine-tuning it on various datasets (SQuAD, TriviaQA, NewsQ, Natural Questions, QuAC)

Language: Jupyter Notebook - Size: 460 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 4 - Forks: 0

pln-fing-udelar/Mask-Align Fork of sgoycoechea/Mask-Align

Fork of THUNLP-MT/Mask-Align to translate NewsQA to Spanish and create NewsQA-es

Language: Python - Size: 62.1 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

pln-fing-udelar/newsqa-es

Code to rebuild the NewsQA-es dataset: a Spanish version of the NewsQA dataset

Language: Python - Size: 25.4 KB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 1

MediaBilly/BERT-Question-Answering

A project about fine-tuning bert-base-uncased model for reading comprehension tasks.

Language: Jupyter Notebook - Size: 273 KB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

smitkiri/news-qa

Reading comprehension based question-answering model for news articles.

Language: Jupyter Notebook - Size: 25.6 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 8 - Forks: 2