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https://github.com/vladmandic/automatic
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cleanup
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@@ -119,7 +119,7 @@ def load_quants(kwargs, repo_id, cache_dir, allow_quant):
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if 'transformer' not in kwargs and model_quant.check_nunchaku('Model'):
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raise NotImplementedError('Nunchaku does not support Chroma Model yet. See https://github.com/mit-han-lab/nunchaku/issues/167')
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elif 'transformer' not in kwargs and model_quant.check_quant('Model'):
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load_args, quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model', device_map=True)
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load_args, quant_args = model_quant.get_dit_args(diffusers_load_config, module='Model', device_map=True, modules_to_not_convert=["distilled_guidance_layer"])
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if quant_args:
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kwargs['transformer'] = diffusers.ChromaTransformer2DModel.from_pretrained(repo_id, subfolder="transformer", **load_args, **quant_args)
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if 'text_encoder' not in kwargs and model_quant.check_nunchaku('TE'):
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