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