distilroberta-bias-onnx
| Property | Value |
|---|---|
| Model Type | Bias Detection |
| Architecture | DistilRoBERTa (ONNX) |
| Author | protectai |
| Model URL | Hugging Face |
What is distilroberta-bias-onnx?
distilroberta-bias-onnx is a specialized ONNX-converted version of the valurank/distilroberta-bias model, designed specifically for detecting bias in text content. This model leverages the efficiency of DistilRoBERTa, a compressed version of RoBERTa, while maintaining high accuracy in bias detection tasks. The conversion to ONNX format enables optimized inference across different hardware platforms.
Implementation Details
The model utilizes the Optimum library for ONNX runtime integration, providing a streamlined approach to bias detection. Implementation requires both the Optimum library and Transformers framework, with the model being accessed through ORTModelForSequenceClassification.
- ONNX-optimized architecture for efficient inference
- Built on DistilRoBERTa base model
- Integrated with 🤗 Optimum library
- Compatible with standard text classification pipelines
Core Capabilities
- Binary classification of text as biased or unbiased
- Score-based bias assessment
- Efficient processing through ONNX optimization
- Integration with LLM Guard for bias scanning
Frequently Asked Questions
Q: What makes this model unique?
This model combines the efficiency of DistilRoBERTa with ONNX optimization, making it particularly suitable for production environments where performance and accuracy in bias detection are crucial.
Q: What are the recommended use cases?
The model is ideal for content moderation, automated bias checking in written content, and integration into larger language model safety systems through LLM Guard. It's particularly useful in scenarios requiring real-time bias detection with efficient resource utilization.
