This repository contains source code for the TaBERT model, a pre-trained language model for learning joint representations of natural language utterances and (semi-)structured tables for semantic parsing. TaBERT is pre-trained on a massive corpus of 26M Web tables and their associated natural language context, and could be used as a drop-in replacement of a semantic parsers original encoder to compute representations for utterances and table schemas (columns).
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Running into GPU out-of-memory issue during pretraining. Any suggestions to reduce GPU memory usage? #17
As title. By the way, I saw there is an argument
empty-cache-freq, would decreasing that help? What would be the side effects of decreasing it?Any inputs are appreciated. Thanks!