THIS PROJECT HAS BEEN ARCHIVED.

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

ONNX version of valurank/distilroberta-bias

This model is a conversion of valurank/distilroberta-bias to ONNX format. It is designed to detect biases in text using the distilled version of the RoBERTa model. The model was converted to ONNX using the πŸ€— Optimum library.

Model Architecture

Base Model: DistilRoBERTa, a distilled version of the RoBERTa model that is optimized for faster performance while maintaining similar accuracy.

Modifications: The model is converted to ONNX format with no additional changes.

Usage

Optimum

Loading the model requires the πŸ€— Optimum library installed.

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


tokenizer = AutoTokenizer.from_pretrained("laiyer/distilroberta-bias-onnx")
model = ORTModelForSequenceClassification.from_pretrained("laiyer/distilroberta-bias-onnx")
classifier = pipeline(
    task="text-classification",
    model=model,
    tokenizer=tokenizer,
)

classifier_output = classifier("Your text to analyze for bias.")
score = (classifier_output[0]["score"] if classifier_output[0]["label"] == "BIASED" else 1 - classifier_output[0]["score"])

LLM Guard

Bias 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
15,213
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for protectai/distilroberta-bias-onnx

Quantized
(3)
this model

Space using protectai/distilroberta-bias-onnx 1

Collection including protectai/distilroberta-bias-onnx