Create handler.py

handler.py

@@ -0,0 +1,22 @@
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
+
+# Global variables to cache model and tokenizer
+model = None
+tokenizer = None
+nlp = None
+
+def init():
+    global model, tokenizer, nlp
+    model_name_or_path = "."
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+    tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+    nlp = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+
+def inference(payload):
+    inputs = payload.get("inputs", "")
+    if not inputs:
+        return {"error": "No inputs provided"}
+
+    # Run generation pipeline
+    outputs = nlp(inputs, max_length=256)
+    return outputs