diff --git a/transcription-api/backends/fasterwhisper.py b/transcription-api/backends/fasterwhisper.py
index f6db2c4..c32181d 100644
--- a/transcription-api/backends/fasterwhisper.py
+++ b/transcription-api/backends/fasterwhisper.py
@@ -6,11 +6,11 @@
 from faster_whisper import WhisperModel, download_model, decode_audio
 
 class FasterWhisperBackend(Backend):
-    device: str = "cpu"  # cpu, cuda
-    quantization: str = "int8"  # int8, float16
+    device: str = 'cpu'  # cpu, cuda? (not working)
+    quantization: str = "default"  # default,int8,float16,float32
     model: WhisperModel | None = None
 
-    def __init__(self, model_size, device: str = "cpu"):
+    def __init__(self, model_size, device: str = None):
         self.model_size = model_size
         self.device = device
         self.__post_init__()
@@ -26,8 +26,8 @@ def model_path(self) -> str:
             raise RuntimeError(f"model not found in {local_model_path}")
         
     def load(self) -> None:
-        # Get CPU threads env variable or default to 4
-        cpu_threads = int(os.environ.get("CPU_THREADS", 4))
+        # Get CPU threads env variable or default to 6
+        cpu_threads = int(os.environ.get("CPU_THREADS", 6))
         self.model = WhisperModel(
             self.model_path(), device=self.device, compute_type=self.quantization, cpu_threads=cpu_threads
         )
@@ -40,10 +40,13 @@ def get_model(self) -> None:
         if not os.path.exists(local_model_path):
             os.makedirs(local_model_path)
         try:
+            print("Model check start...")
             download_model(self.model_size, output_dir=local_model_path, local_files_only=True, cache_dir=local_model_cache)
-            print("Model already cached...")
+            print("Model ceck ended...")
         except:
+            print("Model download start...")
             download_model(self.model_size, output_dir=local_model_path, local_files_only=False, cache_dir=local_model_cache)
+            print("Model download ended.")
 
     def transcribe(
         self, input: np.ndarray, silent: bool = False, language: str = None
@@ -96,4 +99,4 @@ def transcribe(
             "duration": info.duration,
             "segments": result,
         }
-        return transcription
\ No newline at end of file
+        return transcription