  In this paper, we formulate the problem of predicting a geolocation from free
text as a sequence-to-sequence problem. Using this formulation, we obtain a
geocoding model by training a T5 encoder-decoder transformer model using free
text as an input and geolocation as an output. The geocoding model was trained
on geo-tagged wikidump data with adaptive cell partitioning for the geolocation
representation. All of the code including Rest-based application, dataset and
model checkpoints used in this work are publicly available.
