Update app.py

app.py

@@ -5,7 +5,7 @@ from transformers import pipeline, WhisperForConditionalGeneration, WhisperProce
 # Check if a GPU is available and set the device
 device = 0 if torch.cuda.is_available() else -1
 
-# Load the ASR model using the Hugging Face pipeline
+# Load the ASR model and processor
 model_id = "riteshkr/quantized-whisper-large-v3"
 model = WhisperForConditionalGeneration.from_pretrained(model_id)
 processor = WhisperProcessor.from_pretrained(model_id)
@@ -13,7 +13,14 @@ processor = WhisperProcessor.from_pretrained(model_id)
 # Set the language to English using forced_decoder_ids
 forced_decoder_ids = processor.get_decoder_prompt_ids(language="english", task="transcribe")
 
-pipe = pipeline("automatic-speech-recognition", model=model, processor=processor, device=device)
+# Create the pipeline, explicitly setting the tokenizer and feature extractor
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model=model,
+    tokenizer=processor.tokenizer,  # Use the processor's tokenizer
+    feature_extractor=processor.feature_extractor,  # Use the processor's feature extractor
+    device=device
+)
 
 # Define the transcription function
 def transcribe_speech(filepath):