Update app.py

app.py

@@ -12,29 +12,9 @@ app = FastAPI()
 
 # Load the Whisper model once during startup
 device = 0 if torch.cuda.is_available() else -1  # Use GPU if available, otherwise CPU
-# asr_pipeline = pipeline(model="openai/whisper-small", device=device)  # Initialize Whisper model
+asr_pipeline = pipeline(model="openai/whisper-tiny", device=device)  # Initialize Whisper model
 # asr_pipeline = pipeline( model="openai/whisper-small", device=device, language="pt")
 
-# 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 = 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, 
-    tokenizer=tokenizer,  # Pass the tokenizer explicitly
-    feature_extractor=processor.feature_extractor,  # Pass the feature extractor explicitly
-    device=device
-)
 
 # Basic GET endpoint
 @app.get("/")