Create app.py

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model_name = "your-username/nli-mdeberta-model"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def predict(premise, hypothesis):
+    inputs = tokenizer(premise, hypothesis, return_tensors="pt", truncation=True)
+    outputs = model(**inputs)
+    prediction = outputs.logits.softmax(-1)[0]
+    return {"Entailment": prediction[0].item(),
+            "Neutral": prediction[1].item(),
+            "Contradiction": prediction[2].item()}
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=["text", "text"],
+    outputs="label",
+    title="NLI Classifier"
+)
+
+demo.launch()