Upload handler.py

handler.py

@@ -0,0 +1,18 @@
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+import os
+
+class EndpointHandler:
+    def __init__(self, path=""):
+        self.tokenizer = AutoTokenizer.from_pretrained(path)
+        self.model = AutoModelForCausalLM.from_pretrained(path, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+        self.model.eval()
+
+    def __call__(self, inputs: dict):
+        prompt = inputs.get("inputs", "")
+        if not prompt:
+            return {"error": "No input provided."}
+        input_ids = self.tokenizer(prompt, return_tensors="pt").input_ids
+        outputs = self.model.generate(input_ids=input_ids, max_new_tokens=100)
+        generated = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return {"generated_text": generated}