code: def data_gen():
      # Generated from following code snippet
      #
      # from transformers import AutoModelForCausalLM, AutoTokenizer
      # tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1")
      # input = 'My favourite condiment is vinegar' (last two words repeated to satisfy length requirement)
      # tokenized_input = tokenizer([input], return_tensors="pt")
      # input_ids = tokenized_input['input_ids']
      # attention_mask = tokenized_input['attention_mask']
      input_ids = torch.tensor(
          [[1, 1984, 16020, 2076, 2487, 349, 21375, 4749]],
          dtype=torch.int64,
      )
      attention_mask = torch.tensor(
          [[1, 1, 1, 1, 1, 1, 1, 1]], dtype=torch.int64
      )
      return dict(input_ids=input_ids, attention_mask=attention_mask)
  
imports: import torch
  import transformers
  from transformers import MistralConfig
  from ..registry import ModelAttribute, model_zoo
label_desc: Use image node_id 1 for calling a global function with example usage: data_gen() and returns: dict