code: def test_model_13b_logits(self):
      input_ids = [1, 306, 4658, 278, 6593, 310, 2834, 338]
      model = LlamaForCausalLM.from_pretrained(
          "meta-llama/Llama-2-13b-hf", device_map="auto"
      )
      out = model(torch.tensor(input_ids))
      # Expected mean on dim = -1
      EXPECTED_MEAN = torch.tensor(
          [
              [
                  -2.0622,
                  -1.2794,
                  -1.1638,
                  -0.9788,
                  -1.4603,
                  -1.0238,
                  -1.7893,
                  -1.4411,
              ]
          ]
      )
      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([-8.1406, -8.0547, 2.7461, -1.2344, -0.1448, -1.8262, -1.0020, -1.8154, -1.6895, -1.8516, -2.3574, -0.9277, 3.7598, 6.5742, -1.2998, -0.1177, -8.1406, -2.9688, -2.9199, -3.1699, -3.5254, -2.3555, -2.7988, -3.4141, -2.8262, -4.5195, -3.3379, -3.3164, -2.7832, -3.0273])  # fmt: skip
      torch.testing.assert_close(
          out[0, 0, :30], EXPECTED_SLICE, atol=1e-5, rtol=1e-5
      )
  
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 2 for calling the LlamaIntegrationTest obj's underlying member method code with example usage: obj.test_model_13b_logits() without return types