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import gradio as gr
from transformers import pipeline
import torch
classifier = pipeline(
"text-classification",
model="Tirath5504/IPD-finetuned-english-text",
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 with Fine-Tuned Model")
# 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()
iface = gr.Interface(
fn=classify_text,
inputs=gr.Textbox(label="Input Text"),
outputs=[gr.Textbox(label="Predicted Label"), gr.Number(label="Prediction Score")],
title="Hate Speech Classification with Fine-Tuned Model"
)
iface.launch() |