content: from . import samplers
  from .trellis_image_to_3d import TrellisImageTo3DPipeline
  
  
  def from_pretrained(path: str):
      """
      Load a pipeline from a model folder or a Hugging Face model hub.
  
      Args:
          path: The path to the model. Can be either local path or a Hugging Face model name.
      """
      import os
      import json
      is_local = os.path.exists(f"{path}/pipeline.json")
  
      if is_local:
          config_file = f"{path}/pipeline.json"
      else:
          from huggingface_hub import hf_hub_download
          config_file = hf_hub_download(path, "pipeline.json")
  
      with open(config_file, 'r') as f:
          config = json.load(f)
      return globals()[config['name']].from_pretrained(path)
  