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grammatical-error-correction-quantized
leslyarun/grammatical-error-correction-quantized
grammatical-error-correction-quantized is a machine learning model from leslyarun. 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.
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.onnx644 MB · 100%
At a glance
- Library
- transformers
- Model type
- t5
- Access
- Public
- Created
- Oct 28, 2022
- Updated
- Oct 28, 2022
- SHA
- 86c41d15
Model card
From the Hugging Face model README
Get Grammatical corrections on your English text, trained on a subset of c4-200m dataset - ONNX Quantized Model
Use the below code for running the model
from transformers import AutoTokenizer
from optimum.onnxruntime import ORTModelForSeq2SeqLM
from optimum.pipelines import pipeline
tokenizer = AutoTokenizer.from_pretrained("leslyarun/grammatical-error-correction-quantized")
model = ORTModelForSeq2SeqLM.from_pretrained("leslyarun/grammatical-error-correction-quantized",
encoder_file_name="encoder_model_quantized.onnx",
decoder_file_name="decoder_model_quantized.onnx",
decoder_with_past_file_name="decoder_with_past_model_quantized.onnx")
text2text_generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
output = text2text_generator("grammar: " + sentence)
print(output[0]["generated_text"])
- Library
- transformers
- Type
- t5
- Languages
- en
- Created
- Oct 28, 2022
- Updated
- Oct 28, 2022