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Master-Thesis

Enhancing Term Based Document Retrieval by Word Embedding and Transformer Models

Due to space constraint I could not add the ELIB word embedding model and the fine-tuned transformer models. Please download and decompress all three folders into the main branch from this link . Afterwards, download the ft_en_cc model using the following command and place it inside the models folder,

import fasttext.util
fasttext.util.download_model('en', if_exists='ignore')  # English
ft = fasttext.load_model('cc.en.300.bin')