JFLEG: A Fluency Corpus and Benchmark for Grammatical Error Correction
Paper • 1702.04066 • Published
T5 Grammar Correction
This model generates a revised version of inputted text with the goal of containing fewer grammatical errors. It was trained with Happy Transformer using a dataset called JFLEG. Here's a full article on how to train a similar model.
Usage
pip install happytransformer
from happytransformer import HappyTextToText, TTSettings
happy_tt = HappyTextToText("T5", "vennify/t5-base-grammar-correction")
args = TTSettings(num_beams=5, min_length=1)
# Add the prefix "grammar: " before each input
result = happy_tt.generate_text("grammar: This sentences has has bads grammar.", args=args)
print(result.text) # This sentence has bad grammar.
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