code: def test_load_adapter_with_head_from_hub(self):
      model = BertAdapterModel.from_pretrained("bert-base-uncased")
  
      loading_info = {}
      adapter_name = model.load_adapter(
          "qa/squad1@ukp",
          config="houlsby",
          version="1",
          set_active=True,
          loading_info=loading_info,
      )
  
      self.assertEqual(0, len(loading_info["missing_keys"]))
      self.assertEqual(0, len(loading_info["unexpected_keys"]))
  
      self.assertIn(adapter_name, model.adapters_config.adapters)
      # check if config is valid
      expected_hash = get_adapter_config_hash(
          AdapterConfig.load("houlsby")
      )
      real_hash = get_adapter_config_hash(
          model.adapters_config.get(adapter_name)
      )
      self.assertEqual(expected_hash, real_hash)
  
      # check size of output
      in_data = ids_tensor((1, 128), 1000)
      model.to(torch_device)
      output = model(in_data)
      self.assertEqual([1, 128], list(output[0].size()))
  
file_path: adapters/tests/test_adapter_hub.py
imports: import os
  import unittest
  import numpy
  import adapters
  from adapters import ADAPTER_CONFIG_MAP, AdapterConfig, BertAdapterModel, get_adapter_config_hash
  from adapters.trainer import AdapterTrainer
  from adapters.utils import find_in_index
  from transformers import AutoModel, AutoTokenizer, BertForSequenceClassification, GlueDataset, GlueDataTrainingArguments, TrainingArguments, glue_compute_metrics
  from transformers.testing_utils import require_torch, torch_device
  from .test_adapter import ids_tensor
label_desc: Use image node_id 6 for calling the AdapterHubTest obj's underlying member method code with example usage: obj.test_load_adapter_with_head_from_hub() without return types