Update app.py

app.py

@@ -18,14 +18,23 @@ device = 0 if torch.cuda.is_available() else -1  # Use GPU if available, otherwi
 # Load model and processor
 model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small")
 processor = WhisperProcessor.from_pretrained("openai/whisper-small")
+tokenizer = processor.tokenizer  # Explicitly extract the tokenizer from the processor
 
 # Set forced language to Portuguese (pt)
-forced_language_token_id = processor.tokenizer.convert_tokens_to_ids("<|pt|>")
+forced_language_token_id = tokenizer.convert_tokens_to_ids("<|pt|>")
 model.config.forced_decoder_ids = [[2, forced_language_token_id]]  # `2` refers to the decoder start token.
 
-# Initialize the pipeline
-asr_pipeline = pipeline(task="automatic-speech-recognition", model=model, processor=processor, device=device)
 
+# Initialize the pipeline
+# asr_pipeline = pipeline(task="automatic-speech-recognition", model=model, processor=processor, device=device)
+# Initialize the pipeline
+asr_pipeline = pipeline(
+    task="automatic-speech-recognition", 
+    model=model, 
+    tokenizer=tokenizer,  # Pass the tokenizer explicitly
+    feature_extractor=processor.feature_extractor,  # Pass the feature extractor explicitly
+    device=device
+)
 
 # Basic GET endpoint
 @app.get("/")