How to decode wav2vec2 output with beam search?

Beginners
1

I’m running simple wav2vec2 example:

from transformers      import Wav2Vec2ForCTC, Wav2Vec2Processor
from torchaudio.utils  import download_asset

import torch
import librosa

if __name__ == '__main__':
   processor        = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-base-960h")
   model            = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")

   FILE_NAME        = "tutorial-assets/Lab41-SRI-VOiCES-src-sp0307-ch127535-sg0042.wav"
   SPEECH_FILE      = download_asset(FILE_NAME)

   speech, sr       = librosa.load(SPEECH_FILE, sr=16000)
   input_values     = processor(speech, sampling_rate=16000, return_tensors="pt").input_values
   logits           = model(input_values).logits

How can I decode the logits with the beam-search algorithm (without using LM) ?