Update app.py

app.py

@@ -18,10 +18,18 @@ import pyloudnorm as pyln
 # Load the models and tokenizers
 model1 = Wav2Vec2ForCTC.from_pretrained("ai4bharat/indicwav2vec-hindi")
 tokenizer1 = Wav2Vec2Tokenizer.from_pretrained("ai4bharat/indicwav2vec-hindi")
+# Loading the tokenizer and model from Hugging Face's model hub.
 tokenizer = AutoTokenizer.from_pretrained("soketlabs/pragna-1b", token=os.environ.get('HF_TOKEN'))
-model = AutoModelForCausalLM.from_pretrained("soketlabs/pragna-1b", revision='3c5b8b1309f7d89710331ba2f164570608af0de7')
+model = AutoModelForCausalLM.from_pretrained(
+    "soketlabs/pragna-1b", 
+    token=os.environ.get('HF_TOKEN'),
+    revision='3c5b8b1309f7d89710331ba2f164570608af0de7'
+)
 model.load_adapter('soketlabs/pragna-1b-it-v0.1', token=os.environ.get('HF_TOKEN'))
-model.to('cuda')
+
+# using CUDA for an optimal experience
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+model = model.to(device)
 
 # Function to transcribe audio
 def transcribe_audio(audio_data):