Remove the ckpt_path from load_state_dict_guess_config.
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@ -500,9 +500,12 @@ def load_checkpoint(config_path=None, ckpt_path=None, output_vae=True, output_cl
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def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, output_clipvision=False, embedding_directory=None, output_model=True):
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sd = comfy.utils.load_torch_file(ckpt_path)
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return load_state_dict_guess_config(sd, ckpt_path, output_vae, output_clip, output_clipvision, embedding_directory, output_model)
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out = load_state_dict_guess_config(sd, output_vae, output_clip, output_clipvision, embedding_directory, output_model)
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if out is None:
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raise RuntimeError("ERROR: Could not detect model type of: {}".format(ckpt_path))
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return out
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def load_state_dict_guess_config(sd, ckpt_path="<memory>", output_vae=True, output_clip=True, output_clipvision=False, embedding_directory=None, output_model=True):
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def load_state_dict_guess_config(sd, output_vae=True, output_clip=True, output_clipvision=False, embedding_directory=None, output_model=True):
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clip = None
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clipvision = None
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vae = None
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@ -516,7 +519,7 @@ def load_state_dict_guess_config(sd, ckpt_path="<memory>", output_vae=True, outp
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model_config = model_detection.model_config_from_unet(sd, diffusion_model_prefix)
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if model_config is None:
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raise RuntimeError("ERROR: Could not detect model type of: {}".format(ckpt_path))
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return None
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unet_weight_dtype = list(model_config.supported_inference_dtypes)
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if weight_dtype is not None:
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