deberta-v3-base-zeroshot-v1-onnx

[!WARNING] THIS PROJECT HAS BEEN ARCHIVED.

This project and its associated code on GitHub are no longer under active development or maintained.

ONNX version of MoritzLaurer/deberta-v3-base-zeroshot-v1

This model is a conversion of MoritzLaurer/deberta-v3-base-zeroshot-v1 to ONNX format using the 🤗 Optimum library.

MoritzLaurer/deberta-v3-large-zeroshot-v1 is designed for zero-shot classification, capable of determining whether a hypothesis is true or not_true based on a text, a format based on Natural Language Inference (NLI).

Usage

Loading the model requires the 🤗 Optimum library installed.

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


tokenizer = AutoTokenizer.from_pretrained("laiyer/deberta-v3-base-zeroshot-v1-onnx")
model = ORTModelForSequenceClassification.from_pretrained("laiyer/deberta-v3-base-zeroshot-v1-onnx")
classifier = pipeline(
    task="zero-shot-classification",
    model=model,
    tokenizer=tokenizer,
)

classifier_output = classifier("Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.", ["mobile", "website", "billing", "account access"])
print(classifier_output)

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