update test

app.py

@@ -25,16 +25,9 @@ print(f"Using device: {device}")
 
 @spaces.GPU(duration=60 * 2)
 def pipe(file, return_timestamps=False):
-    # model = WhisperForConditionalGeneration.from_pretrained(MODEL_NAME, torch_dtype=torch.float16, low_cpu_mem_usage=True)
-    # model.to(device)
-    # processor = WhisperProcessor.from_pretrained(MODEL_NAME)
-    # model.forward = torch.compile(model.forward, mode="reduce-overhead", fullgraph=True)
-    # model.generation_config.cache_implementation = "static"
     asr = pipeline(
         task="automatic-speech-recognition",
         model=MODEL_NAME,
-        # tokenizer=AutoTokenizer.from_pretrained(MODEL_NAME),
-        # feature_extractor=AutoFeatureExtractor.from_pretrained(MODEL_NAME),
         chunk_length_s=30,
         device=device,
         token=auth_token,
@@ -46,7 +39,6 @@ def pipe(file, return_timestamps=False):
         task="transcribe",
         no_timestamps=not return_timestamps,
     )
-    # asr.model.config.no_timestamps_token_id = asr.tokenizer.encode("<|notimestamps|>", add_special_tokens=False)[0]
     return asr(file, return_timestamps=return_timestamps, batch_size=24)
 
 def transcribe(file, return_timestamps=False):