added custom handler

handler.py

@@ -0,0 +1,20 @@
+from typing import Dict, List, Any
+from transformers import pipeline
+import torch
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        device = 0 if torch.cuda.is_available() else "cpu"
+        self.pipe = pipeline(
+            task="automatic-speech-recognition",
+            model=path,
+            chunk_length_s=30,
+            device=device,
+        )
+
+        self.pipe.model.config.forced_decoder_ids = self.pipe.tokenizer.get_decoder_prompt_ids(language="turkish", task="transcribe")
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        inputs = data.pop("inputs",data)
+        prediction = self.pipe(inputs, return_timestamps=True, generate_kwargs={"language": "turkish", "task": "transcribe"})
+        return prediction