Update app.py

app.py

@@ -1,9 +1,9 @@
 import torch
 import torchaudio
-from transformers import Wav2Vec2ForCTC,Wav2Vec2Processor,pipeline
+from transformers import Wav2Vec2FeatureExtractor,AutoConfig,pipeline
 
-processor = Wav2Vec2Processor.from_pretrained("SeyedAli/Persian-Speech-Emotion-HuBert-V1")
-model = Wav2Vec2ForCTC.from_pretrained("SeyedAli/Persian-Speech-Emotion-HuBert-V1")
+config = AutoConfig.from_pretrained("SeyedAli/Persian-Speech-Emotion-HuBert-V1")
+model = Wav2Vec2FeatureExtractor.from_pretrained("SeyedAli/Persian-Speech-Emotion-HuBert-V1")
 
 def speech_file_to_array_fn(path, sampling_rate):
     speech_array, _sampling_rate = torchaudio.load(path)
@@ -24,7 +24,7 @@ def predict(path, sampling_rate):
     return outputs
 
 def SER(Audio):
-    return predict(Audio,processor.sampling_rate)
+    return predict(Audio,model.sampling_rate)
 
 iface = gr.Interface(fn=SER, inputs="audio", outputs="text")
 iface.launch(share=False)