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

This model is a conversion of MoritzLaurer/deberta-v3-large-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-large-zeroshot-v1-onnx")
tokenizer.model_input_names = ["input_ids", "attention_mask"]
model = ORTModelForSequenceClassification.from_pretrained("laiyer/deberta-v3-large-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)

LLM Guard

Ban Topics scanner

Community

Join our Slack to give us feedback, connect with the maintainers and fellow users, ask questions, or engage in discussions about LLM security!

Downloads last month
17
Inference Examples
Inference API (serverless) has been turned off for this model.

Model tree for protectai/deberta-v3-large-zeroshot-v1-onnx

Quantized
(1)
this model

Datasets used to train protectai/deberta-v3-large-zeroshot-v1-onnx

Collection including protectai/deberta-v3-large-zeroshot-v1-onnx