Update app.py

app.py

@@ -27,14 +27,15 @@ model = pipe
 # Evaluate the model
 # model.eval()
 #print("model.eval ", model.eval())
-
-audio = batch["audio"]
-input_features = processor(audio["array"], sampling_rate=audio["sampling_rate"], return_tensors="pt").input_features
-batch["reference"] = processor.tokenizer._normalize(batch['text'])
-
-
-with torch.no_grad():
-    predicted_ids = model.generate(input_features.to("cuda"))[0]
+def map_to_pred(batch):
+    audio = batch["audio"]
+    input_features = processor(audio["array"], sampling_rate=audio["sampling_rate"], return_tensors="pt").input_features
+    batch["reference"] = processor.tokenizer._normalize(batch['text'])
+    
+    
+    with torch.no_grad():
+        predicted_ids = model.generate(input_features.to("cuda"))[0]
+        
     transcription = processor.decode(predicted_ids)
     batch["prediction"] = processor.tokenizer._normalize(transcription)
     return batch