facebookresearch / TaBERT
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).
Summary
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| Main Code: 5,706 LOC (31 files) = PY (98%) + JAVA (<1%) + YML (<1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 75 LOC (5); Other: 771 LOC (7); |
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| Duplication: 5% | |||
| File Size: 29% long (>1000 LOC), 29% short (<= 200 LOC) | |||
| Unit Size: 13% long (>100 LOC), 36% short (<= 10 LOC) | |||
| Conditional Complexity: 17% complex (McCabe index > 50), 38% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (7 components) | ||
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1 year, 6 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
4 files |
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Latest commit date: 2021-08-11
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