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grammar-t5
vagmi/grammar-t5
grammar-t5 is a machine learning model from vagmi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
This is my first model for grammar error correction. It uses the jfleg dataset and is built on t5-base. It is trained only for 3 epochs so the output isn't that great.
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Aug 3, 2023
- Updated
- Aug 3, 2023
- SHA
- 88634bce
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Datasets
Model card
From the Hugging Face model README
This is my first model for grammar error correction. It uses the jfleg dataset and is built on t5-base. It is trained only for 3 epochs so the output isn't that great.
Usage
You can use this model with the standard transformers library. This model should be small enough to run on the CPU.
$ pip install transformers torch sentencepiece
Once you have the dependencies setup, you should be able to run this model.
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.
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Aug 3, 2023
- Updated
- Aug 3, 2023