first commit

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load your model
+classifier = pipeline("text-classification", model="sachin6624/bert-trainer")
+
+# Map labels to custom messages
+label_mapping = {
+    "LABEL_1": "The sentences are paraphrases (similar in meaning).",
+    "LABEL_0": "The sentences are not paraphrases (different in meaning)."
+}
+
+# Custom prediction function
+def predict(sentence1, sentence2):
+    input_text = f"{sentence1} [SEP] {sentence2}"
+    result = classifier(input_text)
+    label = result[0]["label"]
+    # Return the custom message for the predicted label
+    return label_mapping.get(label, "Unknown label")
+
+# Gradio interface
+interface = gr.Interface(
+    fn=predict,
+    inputs=["text", "text"],
+    outputs="text",  # Output is text for custom messages
+    title="Paraphrase Classification"
+)
+
+# Launch the app
+interface.launch()