Grammar T5

🚀 Grammar Error Correction Model

This is a grammar error correction model that addresses grammar issues in text. It leverages the jfleg dataset and is built upon the t5-base architecture.

🚀 Quick Start

This model can be used with the standard transformers library and is small enough to run on a CPU.

📦 Installation

First, install the necessary dependencies:

$ pip install transformers torch sentencepiece

💻 Usage Examples

Basic Usage

Once the dependencies are set up, you can run the model as follows:

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

model_name = 'vagmi/grammar-t5'

model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

text = 'fix grammar: I am work with machine to write gooder english.'
inputs = tokenizer(text, return_tensors='pt')
outputs = model.generate(inputs['input_ids'], num_beams=2, max_length=512, early_stopping=True)
fixed = tokenizer.decode(outputs[0], skip_special_tokens=True)
# I am working with machine to write better english.

📄 License

This project is licensed under the Apache-2.0 license.