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Update README.md

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@@ -81,7 +81,11 @@ input_dic['spectrogram'] = torch.from_numpy(lms).unsqueez(dim=0).to(device)
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  model.eval()
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  gen_ids = model.forward_test(input)
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  gen_text = model.neck.tokenizer.batch_decode(gen_ids.clip(0))
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-
 
 
 
 
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  print(gen_text)
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  ```
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  model.eval()
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  gen_ids = model.forward_test(input)
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  gen_text = model.neck.tokenizer.batch_decode(gen_ids.clip(0))
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+ # 4. Post-processing
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+ # Due to the training data, the generated texts will have some bias and require simple post-processing.
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+ gen_text = gen_text.split('<s>')[-1].split('\n')[0].strip()
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+ gen_text = gen_text.replace(' in Chinese','')
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+ gen_text = gen_text.replace(' Chinese','')
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  print(gen_text)
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  ```
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