Neo87z1/STEKGramarChecker

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.