code: def filter_parameters(model, filter_string):
      return {
          k: v
          for (k, v) in model.named_parameters()
          if filter_string in k
      }
  
file_path: adapters/tests/test_adapter_embeddings.py
imports: import copy
  import tempfile
  import torch
  from adapters import AutoAdapterModel
  from transformers import AutoTokenizer, Trainer, TrainingArguments
  from transformers.testing_utils import require_torch, torch_device
label_desc: Use image node_id 1 for calling a global function with example usage: filter_parameters(model, filter_string) and returns: unknown