Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+# Load model and tokenizer from Hugging Face
+model = AutoModelForSeq2SeqLM.from_pretrained("your-hf-username/bart-positive-tone-finetuned")
+tokenizer = AutoTokenizer.from_pretrained("your-hf-username/bart-positive-tone-finetuned")
+
+# Function to process headlines
+def neutralize_headline(headline):
+    inputs = tokenizer(headline, return_tensors="pt", truncation=True, padding=True)
+    outputs = model.generate(**inputs)
+    neutralized_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return neutralized_text
+
+# Create Gradio UI
+iface = gr.Interface(
+    fn=neutralize_headline,
+    inputs=gr.Textbox(lines=2, placeholder="Enter a negative/extreme headline..."),
+    outputs="text",
+    title="Headline Neutralizer",
+    description="Converts extreme headlines into a neutral tone.",
+)
+
+iface.launch()