ruffed

app.py

@@ -26,7 +26,9 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
 # Load the model
-asr_model = HubertForCTC.from_pretrained(model_name, torch_dtype=torch_dtype, device_map=device)
+asr_model = HubertForCTC.from_pretrained(
+    model_name, torch_dtype=torch_dtype, device_map=device
+)
 processor = Wav2Vec2Processor.from_pretrained(model_name)
 
 if use_torch_compile:
@@ -159,7 +161,9 @@ def inference(audio_path, progress=gr.Progress()):
 
         audio_input = audio_input.squeeze(0).numpy()
 
-        inputs = processor([audio_input], sampling_rate=16_000, padding=True).input_values
+        inputs = processor(
+            [audio_input], sampling_rate=16_000, padding=True
+        ).input_values
         features = torch.tensor(np.array(inputs), dtype=torch_dtype).to(device)
 
         with torch.inference_mode():