code: def test_model_7b_logits(self):
      input_ids = [1, 306, 4658, 278, 6593, 310, 2834, 338]
      model = LlamaForCausalLM.from_pretrained(
          "meta-llama/Llama-2-7b-hf", device_map="auto"
      )
      out = model(torch.tensor([input_ids]))
      # Expected mean on dim = -1
      EXPECTED_MEAN = torch.tensor(
          [
              [
                  -6.6550,
                  -4.1227,
                  -4.9859,
                  -3.2406,
                  0.8262,
                  -3.0033,
                  1.2964,
                  -3.3699,
              ]
          ]
      )
      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([-12.8281, -7.4453, -0.4639, -8.0625, -7.2500, -8.0000, -6.4883, -7.7695, -7.8438, -7.0312, -6.2188, -7.1328, -1.8496, 1.9961, -8.6250, -6.7227, -12.8281, -6.9492, -7.0742, -7.7852, -7.5820, -7.9062, -6.9375, -7.9805, -8.3438, -8.1562, -8.0469, -7.6250, -7.7422, -7.3398,])  # 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 1 for calling the LlamaIntegrationTest obj's underlying member method code with example usage: obj.test_model_7b_logits() without return types