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
    }
]

Disclaimer

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.