code: def test_jitted_tiny_llama(self):
      old_float = dtypes.default_float
      dtypes.default_float = dtypes.float16
  
      args_tiny = {
          "dim": 1024,
          "hidden_dim": 1024,
          "n_heads": 8,
          "n_layers": 8,
          "norm_eps": 1e-05,
          "vocab_size": 1000,
      }
      model = Transformer(**args_tiny)
      derandomize_model(model)
  
      def test(t):
          return model(t, 0).realize()
  
      @TinyJit
      def test_jit(t):
          return model(t, 0).realize()
  
      helper_test_jitted_correctness(
          lambda: (
              Tensor(
                  [
                      [
                          1,
                      ]
                  ]
              ),
          ),
          test,
          test_jit,
      )
      dtypes.default_float = old_float
  
file_path: tinygrad/test/external/external_test_jit_on_models.py
imports: import unittest
  import numpy
  from tinygrad import Tensor, dtypes
  from tinygrad.jit import TinyJit
  from tinygrad.helpers import CI
  from test.helpers import derandomize_model
  from examples.llama import Transformer
label_desc: Use image node_id 1 for calling the TestJittedModels obj's underlying member method code with example usage: obj.test_jitted_tiny_llama() and returns: model, model