Update app.py

app.py

@@ -16,14 +16,6 @@ model = Wav2Vec2ForCTC.from_pretrained(MODEL_NAME).to(device)
 processor = Wav2Vec2Processor.from_pretrained(MODEL_NAME) # do i need this? can't remember
 
 
-
-#def greet(name):
-#    return "Hello " + name + "!!"
-#iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-#iface.launch()
-#api = gr.Interface.load("models/carlosdanielhernandezmena/wav2vec2-large-xlsr-53-icelandic-ep10-1000h")
-#iface.launch()
-
 #ds = load_dataset("language-and-voice-lab/samromur_asr",split='train',streaming=True)
 #ds = load_dataset("language-and-voice-lab/samromur_asr",split='test')
 #ds = ds.cast_column("audio", Audio(sampling_rate=16_000))
@@ -42,9 +34,9 @@ def recc(a_f):
         wav = signal.resample(wav, wlen)
         
     with torch.inference_mode():
-        wav = torch.from_numpy(wav).unsqueeze(0)
-        if torch.cuda.is_available():
-            wav = wav.cuda()
+        #wav = torch.from_numpy(wav).unsqueeze(0)
+        #if torch.cuda.is_available():
+        #    wav = wav.cuda()
         input_values = processor(wav,sampling_rate=16000).input_values[0]
         input_values = torch.tensor(input_values, device=device).unsqueeze(0)
         logits = model(input_values).logits