Update handler.py

handler.py

@@ -81,5 +81,5 @@ class EndpointHandler():
 
                 outputs.append({'logit': torch.softmax(output.logits, dim=1)[0][1].float().cpu().data.numpy().max(), 'start_time_s': segment*15})
 
-        outputs = {'logit': max([x['logit'] for x in outputs]), 'classification': 'present' if max([x['logit'] for x in outputs]) >= self.threshold else 'absent', 'model_id': 'DORI-SRKW/whisper-base-mm-cpu'}
+        outputs = {'logit': max([x['logit'] for x in outputs]), 'classification': 'present' if max([x['logit'] for x in outputs]) >= self.threshold else 'absent', 'model_id': 'DORI-SRKW/whisper-tiny-mm-cpu'}
         return outputs