 Usage: ```py from transformers import AutoTokenizer, T5ForConditionalGeneration  MODEL_CKPT = "mrm8488/t5-small-finetuned-text2log"  model = T5ForConditionalGeneration.from_pretrained(MODEL_CKPT).to(device) tokenizer = AutoTokenizer.from_pretrained(MODEL_CKPT)  def translate(text):     inputs = tokenizer(text, padding="longest", max_length=64, return_tensors="pt")     input_ids = inputs.input_ids.to(device)     attention_mask = inputs.attention_mask.to(device)      output = model.generate(input_ids, attention_mask=attention_mask, early_stopping=False, max_length=64)      return tokenizer.decode(output[0], skip_special_tokens=True)  prompt_nl_to_fol = "translate to fol: " prompt_fol_to_nl = "translate to nl: " example_1 = "Every killer leaves something." example_2 = "all x1.(_woman(x1) -> exists x2.(_emotion(x2) & _experience(x1,x2)))"  print(translate(prompt_nl_to_fol + example_1)) 