chunk_content: as np
  import gc
  
  eval_dataloader = DataLoader(common_voice["test"], batch_size=8, collate_fn=data_collator)
  
  model.eval()
  for step, batch in enumerate(tqdm(eval_dataloader)):
      with torch.cuda.amp.autocast():
          with torch.no_grad():
              generated_tokens = (
                  model.generate(
                      input_features=batch["input_features"].to("cuda"),
                      decoder_input_ids=batch["labels"][:, :4].to("cuda")