Create handler.py

handler.py

@@ -0,0 +1,15 @@
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+class Handler:
+    def __init__(self):
+        self.model = AutoModelForSequenceClassification.from_pretrained(".")
+        self.tokenizer = AutoTokenizer.from_pretrained(".")
+        self.labels = ["presentation","projects","skills","education","contact","fallback"]
+
+    def inference(self, inputs):
+        encoded = self.tokenizer(inputs, return_tensors="pt")
+        with torch.no_grad():
+            logits = self.model(**encoded).logits
+        predicted_class = torch.argmax(logits, dim=1).item()
+        return {"label": self.labels[predicted_class], "score": 1.0}  # score simplifié