Update app.py

app.py

@@ -1,7 +1,31 @@
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("BenTouss/mdeberta-eurochef")
+model = AutoModelForSequenceClassification.from_pretrained("BenTouss/mdeberta-eurochef")
+
+def get_labels(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=256)
+    
+    # Get predictions
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.sigmoid(outputs.logits)[0]
+    
+    # Get predicted labels (threshold = 0.6)
+    predicted_labels = []
+    for idx, prob in enumerate(probs):
+        if prob > 0.6:
+            label = model.config.id2label[idx]
+            predicted_labels.append((label, prob.item()))
+    
+    return predicted_labels
+
 
 def greet(name):
     return "Hello " + name + "!!"
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo = gr.Interface(fn=get_labels, inputs="text", outputs="text")
 demo.launch()