Update app.py

app.py

@@ -1,11 +1,11 @@
 import gradio as gr
-from transformers import AutoModelForCTC, AutoFeatureExtractor
 import torch
 import librosa
 import re
 
 print("Loading MedASR model...")
-feature_extractor = AutoFeatureExtractor.from_pretrained("google/medasr", trust_remote_code=True)
+from transformers import AutoModelForCTC, AutoProcessor
+processor = AutoProcessor.from_pretrained("google/medasr", trust_remote_code=True)
 model = AutoModelForCTC.from_pretrained("google/medasr", trust_remote_code=True)
 print("MedASR loaded!")
 
@@ -20,11 +20,11 @@ def transcribe(audio_path):
         return "No audio provided"
     try:
         speech, sr = librosa.load(audio_path, sr=16000)
-        inputs = feature_extractor(speech, sampling_rate=16000, return_tensors="pt", padding=True)
+        inputs = processor(speech, sampling_rate=16000, return_tensors="pt", padding=True)
         with torch.no_grad():
             logits = model(**inputs).logits
             ids = torch.argmax(logits, dim=-1)
-            raw = feature_extractor.tokenizer.decode(ids[0], skip_special_tokens=True)
+            raw = processor.batch_decode(ids)[0]
         return clean_transcription(raw)
     except Exception as e:
         return f"Error: {str(e)}"