protectai/deberta-v3-large-zeroshot-v1-onnx
By protectai · ↓ 12 · ♥ 1 · Updated 2024-04-11
What's in this repo
This page lists the files in protectai/deberta-v3-large-zeroshot-v1-onnx, including model.onnx.
- 1 ONNX models (.onnx files)
- 11 files, including 6 .json, 1 .md, 1 .txt, 1 .onnx, 1 .model
- Last updated 2024-04-11
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
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)
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Model info
Created: 2023-11-12
Updated: 2024-04-11
View on Hugging Face