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1e225c4 a16f964 4e66a4e a16f964 1e225c4 a16f964 4e66a4e 1e225c4 4e66a4e a70dc7d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | import gradio as gr
from transformers import pipeline, AutoTokenizer
# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained('prabhaskenche/toxic-comment-classification-using-RoBERTa')
classifier = pipeline(
'text-classification',
model='prabhaskenche/toxic-comment-classification-using-RoBERTa',
tokenizer=tokenizer,
top_k=None # Use top_k=None to get all scores
)
def classify(text):
results = classifier(text)
# Assuming LABEL_0 is non-toxic and LABEL_1 is toxic
non_toxic_score = next((item['score'] for item in results[0] if item['label'] == 'LABEL_0'), 0)
toxic_score = next((item['score'] for item in results[0] if item['label'] == 'LABEL_1'), 0)
return f"{non_toxic_score:.3f} non-toxic, {toxic_score:.3f} toxic"
# Create the Gradio interface
interface = gr.Interface(
fn=classify,
inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
outputs="text"
)
# Launch the interface
interface.launch()
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