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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)
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