docstr: Test the generation quality of the quantized model and see that we are matching the expected output.
  Given that we are operating on small numbers + the testing model is relatively small, we might not get
  the same output across GPUs. So we'll generate few tokens (5-10) and check their output.
code: def test_generate_quality(self):
      r"""
      Test the generation quality of the quantized model and see that we are matching the expected output.
      Given that we are operating on small numbers + the testing model is relatively small, we might not get
      the same output across GPUs. So we'll generate few tokens (5-10) and check their output.
      """
      encoded_input = self.tokenizer(
          self.input_text, return_tensors="pt"
      )
  
      output_sequences = self.model_4bit.generate(
          input_ids=encoded_input["input_ids"].to(
              self.model_4bit.device
          ),
          max_new_tokens=10,
      )
  
      self.assertIn(
          self.tokenizer.decode(
              output_sequences[0], skip_special_tokens=True
          ),
          self.EXPECTED_OUTPUTS,
      )
  
imports: import gc
  import tempfile
  import unittest
  import torch
  import torch.nn
  from accelerate import Accelerator, init_empty_weights
  from accelerate.test_utils import require_bnb, require_cuda, require_huggingface_suite, require_multi_gpu, slow
  from accelerate.utils.bnb import load_and_quantize_model
  from accelerate.utils.dataclasses import BnbQuantizationConfig
label_desc: Use image node_id 5 for calling the Bnb4BitTestLoadedModel obj's underlying member method code with example usage: obj.test_generate_quality() without return types