Roberta Base Ai Text Detection V1

🚀 RoBERTa-base AI Text Detector

A fine-tuned RoBERTa-base model designed to detect AI-generated English texts.

This model offers a reliable solution for distinguishing between AI-generated and human-written English texts, leveraging the power of the RoBERTa-base architecture.

🚀 Quick Start

✨ Features

• AI Text Detection: Specifically fine-tuned to detect AI-generated English texts.
• Pipeline Integration: Can be directly used with a pipeline for seamless integration.

📦 Installation

No explicit installation steps are provided in the original document. However, to use this model, you need to have the transformers library installed. You can install it via pip:

pip install transformers

💻 Usage Examples

Basic Usage

You can use this model directly with a pipeline. For better performance, you should apply the clean_text function in utils.py.

from transformers import pipeline
from utils import clean_text

classifier = pipeline(
    "text-classification",
    model="fakespot-ai/roberta-base-ai-text-detection-v1"
)

# single text
text = "text 1"
classifier(clean_text(text))
[   
    {
        'label': str,
      'score': float
    }
]

# list of texts
texts = ["text 1", "text 2"]
classifier([clean_text(t) for t in texts])
[   
    {
        'label': str,
      'score': float
    },
    {
        'label': str,
      'score': float
    }
]

📚 Documentation

See FakespotAILabs/ApolloDFT for more details and a technical report of the model and experiments we conducted.

📄 License

This project is licensed under the Apache-2.0 license.

⚠️ Important Note

• The model's score represents an estimation of the likelihood of the input text being AI-generated or human-written, rather than indicating the proportion of the text that is AI-generated or human-written.
• The accuracy and performance of the model generally improve with longer text inputs.