code: def __init__(self, cache_config: CacheConfig):
      self.cache = Cache(cache_config)
      self.model_server_instances: Dict[str, HuggingFaceServer] = {}
  
imports: from copy import deepcopy
  import torch
  from dataclasses import asdict
  from transformers import AutoModelForCausalLM, AutoTokenizer
  from typing import Any, Dict, List
  from helm.common.cache import Cache, CacheConfig
  from helm.common.hierarchical_logger import htrack_block, hlog
  from helm.common.request import EMBEDDING_UNAVAILABLE_REQUEST_RESULT, Request, RequestResult, Sequence, Token
  from helm.common.tokenization_request import TokenizationRequest, TokenizationRequestResult, DecodeRequest, DecodeRequestResult, TokenizationToken
  from .client import Client, wrap_request_time, truncate_sequence
  from .huggingface_tokenizer import HuggingFaceTokenizers
  from helm.proxy.clients.huggingface_model_registry import HuggingFaceModelConfig, get_huggingface_model_config
label_desc: Use image node_id 1 to create a new HuggingFaceClient object from inherited base classes: Client with example: obj = HuggingFaceClient(cache_config)