class_docstr: Initialize a new Inference Client.
  
  [`InferenceClient`] aims to provide a unified experience to perform inference. The client can be used
  seamlessly with either the (free) Inference API or self-hosted Inference Endpoints.
  
  Args:
      model (`str`, `optional`):
          The model to run inference with. Can be a model id hosted on the Hugging Face Hub, e.g. `bigcode/starcoder`
          or a URL to a deployed Inference Endpoint. Defaults to None, in which case a recommended model is
          automatically selected for the task.
      token (`str`, *optional*):
          Hugging Face token. Will default to the locally saved token. Pass `token=False` if you don't want to send
          your token to the server.
      timeout (`float`, `optional`):
          The maximum number of seconds to wait for a response from the server. Loading a new model in Inference
          API can take up to several minutes. Defaults to None, meaning it will loop until the server is available.
      headers (`Dict[str, str]`, `optional`):
          Additional headers to send to the server. By default only the authorization and user-agent headers are sent.
          Values in this dictionary will override the default values.
      cookies (`Dict[str, str]`, `optional`):
          Additional cookies to send to the server.
code: def _resolve_url(
      self, model: Optional[str] = None, task: Optional[str] = None
  ) -> str:
      model = model or self.model
  
      # If model is already a URL, ignore `task` and return directly
      if model is not None and (
          model.startswith("http://") or model.startswith("https://")
      ):
          return model
  
      # # If no model but task is set => fetch the recommended one for this task
      if model is None:
          if task is None:
              raise ValueError(
                  "You must specify at least a model (repo_id or URL) or a task, either when instantiating"
                  " `InferenceClient` or when making a request."
              )
          model = self.get_recommended_model(task)
          logger.info(
              f"Using recommended model {model} for task {task}. Note that it is"
              f" encouraged to explicitly set `model='{model}'` as the recommended"
              " models list might get updated without prior notice."
          )
  
      # Compute InferenceAPI url
      return (
          # Feature-extraction and sentence-similarity are the only cases where we handle models with several tasks.
          f"{INFERENCE_ENDPOINT}/pipeline/{task}/{model}"
          if task in ("feature-extraction", "sentence-similarity")
          # Otherwise, we use the default endpoint
          else f"{INFERENCE_ENDPOINT}/models/{model}"
      )
  
imports: import logging
  import time
  import warnings
  from dataclasses import asdict
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Literal, Optional, Union, overload
  from requests import HTTPError
  from requests.structures import CaseInsensitiveDict
  from huggingface_hub.constants import ALL_INFERENCE_API_FRAMEWORKS, INFERENCE_ENDPOINT, MAIN_INFERENCE_API_FRAMEWORKS
  from huggingface_hub.inference._common import TASKS_EXPECTING_IMAGES, ContentT, InferenceTimeoutError, ModelStatus, _b64_encode, _b64_to_image, _bytes_to_dict, _bytes_to_image, _bytes_to_list, _fetch_recommended_models, _import_numpy, _is_tgi_server, _open_as_binary, _set_as_non_tgi, _stream_text_generation_response
  from huggingface_hub.inference._text_generation import TextGenerationParameters, TextGenerationRequest, TextGenerationResponse, TextGenerationStreamResponse, raise_text_generation_error
  from huggingface_hub.inference._types import ClassificationOutput, ConversationalOutput, FillMaskOutput, ImageSegmentationOutput, ObjectDetectionOutput, QuestionAnsweringOutput, TableQuestionAnsweringOutput, TokenClassificationOutput
  from huggingface_hub.utils import BadRequestError, build_hf_headers, get_session, hf_raise_for_status
label_desc: Use image node_id 37 for calling the InferenceClient obj's underlying member method code with example usage: obj._resolve_url(model, task) and returns: unknown, model