digitalepidemiologylab/covid-twitter-bert

The model was trained on 160M tweets collected between January 12 and April 16, 2020 containing at least one of the keywords "wuhan", "ncov", "coronavirus", "covid", or "sars-cov-2" These tweets were filtered and preprocessed to reach a final sample of 22.5M tweets (containing 40.7M sentences and 633M tokens) which were used for training . Make sure to use the same text preprocessing as we did for pretraining . This involves replacing user mentions, urls and emojis . You can also use the model with the pipeline interface: pipeline(task='fill-mask,