Update app.py

app.py

@@ -24,11 +24,11 @@ def resampler(input_file_path, output_file_path):
     subprocess.call(command, shell=True)
 
 
-def parse_transcription_with_lm(logits):
-    result = processor_with_LM.batch_decode(logits.cpu().numpy())
-    text = result.text
-    transcription = text[0].replace('<s>','')
-    return transcription
+# def parse_transcription_with_lm(logits):
+#     result = processor_with_LM.batch_decode(logits.cpu().numpy())
+#     text = result.text
+#     transcription = text[0].replace('<s>','')
+#     return transcription
 
 def parse_transcription(logits):
     predicted_ids = torch.argmax(logits, dim=-1)
@@ -41,7 +41,8 @@ def parse(wav_file, applyLM):
         logits = model(**input_values).logits
    
     if applyLM:
-        return parse_transcription_with_lm(logits)
+        # return parse_transcription_with_lm(logits)
+        return "done"
     else:
         return parse_transcription(logits)
 
@@ -64,7 +65,7 @@ model_id = "anuragshas/wav2vec2-large-xlsr-53-odia"
 
 
 processor = Wav2Vec2Processor.from_pretrained(model_id)
-processor_with_LM = Wav2Vec2ProcessorWithLM.from_pretrained(model_id)
+# processor_with_LM = Wav2Vec2ProcessorWithLM.from_pretrained(model_id)
 model = Wav2Vec2ForCTC.from_pretrained(model_id)