Update app.py

app.py

@@ -9,7 +9,7 @@ from transformers import (
 
 # === Config ===
 MODEL_ID = "Omartificial-Intelligence-Space/SA-BERT-Classifier"
-HF_TOKEN = os.getenv("HUGGINGFACE_HUB_TOKEN")  # Get from Secrets
+HF_TOKEN = os.getenv("HUGGINGFACE_HUB_TOKEN")
 DEVICE = 0 if torch.cuda.is_available() else -1
 
 # === Load model and tokenizer ===
@@ -23,21 +23,17 @@ pipeline = TextClassificationPipeline(
     model=model,
     tokenizer=tokenizer,
     device=DEVICE,
-    return_all_scores=True
+    top_k=None  # replaces deprecated return_all_scores
 )
 
-# === Prediction function ===
+# === Inference function ===
 def classify_dialect(text):
     results = pipeline(text)[0]
     scores = {int(item["label"].split("_")[-1]): item["score"] for item in results}
     p_non_saudi = scores.get(0, 0.0)
     p_saudi = scores.get(1, 0.0)
     prediction = "Saudi Dialect" if p_saudi > p_non_saudi else "Non-Saudi Dialect"
-    return {
-        "Saudi Dialect (Probability)": round(p_saudi, 4),
-        "Non-Saudi Dialect (Probability)": round(p_non_saudi, 4),
-        "Final Prediction": prediction
-    }
+    return round(p_saudi, 4), round(p_non_saudi, 4), prediction
 
 # === Gradio Interface ===
 demo = gr.Interface(
@@ -48,8 +44,9 @@ demo = gr.Interface(
         gr.Label(label="Non-Saudi Dialect (Probability)"),
         gr.Textbox(label="Final Prediction")
     ],
-    title="Saudi Dialect Classifier",
-    description="نموذج لتصنيف الجملة هل هي باللهجة السعودية أم لا باستخدام BERT"
+    title="🗣️ Saudi Dialect Classifier",
+    description="🔍 نموذج BERT لتصنيف الجمل إلى لهجة سعودية أو غير سعودية.\n\n👩‍💻 Deployed by **Ayesha Shafique**\n\n🌐 Model credit: [Omartificial-Intelligence-Space](https://huggingface.co/Omartificial-Intelligence-Space)",
+    allow_flagging="never"
 )
 
 # === Launch App ===