code: def test_model_13bf_logits(self):
      input_ids = [1, 306, 4658, 278, 6593, 310, 2834, 338]
      model = LlamaForCausalLM.from_pretrained(
          "meta-llama/Llama-2-13b-chat-hf", device_map="auto"
      )
      out = model(torch.tensor(input_ids))
      # Expected mean on dim = -1
      EXPECTED_MEAN = torch.tensor(
          [
              [
                  -0.8562,
                  -1.8520,
                  -0.7551,
                  -0.4162,
                  -1.5161,
                  -1.2038,
                  -2.4823,
                  -2.3254,
              ]
          ]
      )
      torch.testing.assert_close(
          out.mean(-1), EXPECTED_MEAN, atol=1e-2, rtol=1e-2
      )
      # slicing logits[0, 0, 0:30]
      EXPECTED_SLICE = torch.tensor([-2.2227, 4.8828, 0.9023, -0.4578, -0.7871, -0.1033, -0.6221, -0.5786, -0.7803, -1.0674, -1.2920, -0.1570, 0.8008, 2.0723, -0.9497, 0.2771, -2.2227, -0.7612, -1.4346, -1.2061, -1.6426, -0.3000, -0.7139, -1.1934, -1.8691, -1.6973, -1.5947, -1.2705, -0.3523, -0.5513])  # fmt: skip
      torch.testing.assert_close(
          out.mean(-1), EXPECTED_SLICE, atol=1e-2, rtol=1e-2
      )
  
imports: import tempfile
  import unittest
  import pytest
  from parameterized import parameterized
  from transformers import LlamaConfig, is_torch_available, set_seed
  from transformers.testing_utils import require_bitsandbytes, require_flash_attn, require_torch, require_torch_accelerator, require_torch_gpu, require_torch_sdpa, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 3 for calling the LlamaIntegrationTest obj's underlying member method code with example usage: obj.test_model_13bf_logits() without return types