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import gradio as gr | |
from transformers import pipeline | |
import torch | |
classifier = pipeline( | |
"text-classification", | |
model="Tirath5504/IPD-Text-Hinglish", | |
device=0 if torch.cuda.is_available() else -1 | |
) | |
def classify_text(text): | |
result = classifier(text) | |
return result[0]['label'], result[0]['score'] | |
with gr.Blocks() as demo: | |
gr.Markdown("# Hate Speech Classification of Hinglish Text") | |
with gr.Row(): | |
text_input = gr.Textbox(label="Input Text") | |
label_output = gr.Textbox(label="Predicted Label") | |
score_output = gr.Number(label="Prediction Score") | |
text_input.change(fn=classify_text, inputs=text_input, outputs=[label_output, score_output]) | |
demo.launch() |