Update handler.py

handler.py

@@ -5,31 +5,31 @@ from transformers import WhisperProcessor, AutoModelForSpeechSeq2Seq, AutoProces
 
 class EndpointHandler():
     def __init__(self, path=""):
-        device = "cuda:0" if torch.cuda.is_available() else "cpu"
-        torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
-        model_id = path
+        #device = "cuda:0" if torch.cuda.is_available() else "cpu"
+        #torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+        #model_id = path
 
-        model = AutoModelForSpeechSeq2Seq.from_pretrained(
-            model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
-        )
-        model.to(device)
+        #model = AutoModelForSpeechSeq2Seq.from_pretrained(
+        #    model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
+        #)
+        #model.to(device)
 
-        processor = AutoProcessor.from_pretrained(model_id)
+        #processor = AutoProcessor.from_pretrained(model_id)
         #processor = WhisperProcessor.from_pretrained(model_id)
         
-        self.pipeline = pipeline(
-            "automatic-speech-recognition",
-            model=model,
-            tokenizer=processor.tokenizer,
-            feature_extractor=processor.feature_extractor,
-            max_new_tokens=128,
-            chunk_length_s=30,
-            batch_size=16,
-            return_timestamps=True,
-            torch_dtype=torch_dtype,
-            device=device,
-        )
-        self.model = model
+        #self.pipeline = pipeline(
+        #    "automatic-speech-recognition",
+        #    model=model,
+        #    tokenizer=processor.tokenizer,
+        #    feature_extractor=processor.feature_extractor,
+        #    max_new_tokens=128,
+        #    chunk_length_s=30,
+        #    batch_size=16,
+        #    return_timestamps=True,
+        #    torch_dtype=torch_dtype,
+        #    device=device,
+        #)
+        #self.model = model
 
 
     def __call__(self, data: Dict[str, bytes]) -> Dict[str, str]: