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This model represents an ONNX-optimized version of the original roberta-base-formality-ranker model. It has been specifically tailored for GPUs and may exhibit variations in performance when run on CPUs.

Dependencies

Please install the following dependency before you begin working with the model:

pip install optimum[onnxruntime-gpu]

How to use

from transformers import AutoTokenizer
from optimum.onnxruntime import ORTModelForSequenceClassification
from optimum.pipelines import pipeline

# load tokenizer and model weights
tokenizer = AutoTokenizer.from_pretrained('Deepchecks/roberta_base_formality_ranker_onnx')
model = ORTModelForSequenceClassification.from_pretrained('Deepchecks/roberta_base_formality_ranker_onnx')

# prepare the pipeline and generate inferences
user_inputs = ["I hope this email finds you well", "I hope this email find you swell", "What's up doc?"]
pip = pipeline(task='text-classification', model=model, tokenizer=tokenizer, device=device, accelerator="ort")
res = pip(user_inputs, batch_size=64, truncation="only_first")

Licensing Information

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0

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