Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load zero-shot-classification pipeline
+classifier = pipeline("zero-shot-classification",
+                      model="facebook/bart-large-mnli")  # Can also use 'joeddav/xlm-roberta-large-xnli'
+
+def classify_text(text, labels):
+    candidate_labels = [label.strip() for label in labels.split(",")]
+    result = classifier(text, candidate_labels)
+    return {label: float(f"{score:.3f}") for label, score in zip(result["labels"], result["scores"])}
+
+demo = gr.Interface(
+    fn=classify_text,
+    inputs=[
+        gr.Textbox(lines=3, placeholder="Enter the text to classify...", label="Input Text"),
+        gr.Textbox(lines=1, placeholder="Enter comma-separated labels (e.g., finance, tech, sports)", label="Candidate Labels")
+    ],
+    outputs="label",
+    title="Zero-Shot Text Classification with BART & XLM-RoBERTa",
+    description="Classify text into categories without training data using transformer-based models. Based on the article from C# Corner."
+)
+
+demo.launch()