hello。训练时候报错，pretrain权重没有。这儿填stabilityai/stable-diffusion-xl-base-1.0吗？

[gangxu822]

Repository Not Found for url: https://huggingface.co/None/resolve/main/tokenizer/tokenizer_config.json.
Please make sure you specified the correct repo_id and repo_type.
If you are trying to access a private or gated repo, make sure you are authenticated. For more details, see https://huggingface.co/docs/huggingface_hub/authentication

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "train_GPSDiffusion_sdxl.py", line 1627, in
main(args)
File "train_GPSDiffusion_sdxl.py", line 1027, in main
tokenizer_one = AutoTokenizer.from_pretrained(
File "/opt/nas/p/conda/envs/GPSDiffusion/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 833, in from_pretrained
tokenizer_config = get_tokenizer_config(pretrained_model_name_or_path, **kwargs)
File "/opt/nas/p/conda/envs/GPSDiffusion/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 665, in get_tokenizer_config
resolved_config_file = cached_file(
File "/opt/nas/p/conda/envs/GPSDiffusion/lib/python3.8/site-packages/transformers/utils/hub.py", line 425, in cached_file
raise EnvironmentError(
OSError: None is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo either by logging in with huggingface-cli login or by passing token=<your_token>

[gangxu822]

parser.add_argument(                                                         
    "--pretrained_model_name_or_path",                                       
    type=str,                                                                
    default=None,
    # required=True,
    help="Path to pretrained model or model identifier from huggingface.co/models.",
)                                                                            
parser.add_argument(                                                         
    "--pretrained_vae_model_name_or_path",                                   
    type=str,                                                                
    default='stabilityai/stable-diffusion-xl-base-1.0',                      
    help="Path to an improved VAE to stabilize training. For more details check out: https://github.com/huggingface/diffusers/pull/4038.",
)
parser.add_argument(                                                         
    "--controlnet_model_name_or_path",                                       
    type=str,
    default=None,                                                            
    help="Path to pretrained controlnet model or model identifier from huggingface.co/models."
    " If not specified controlnet weights are initialized from unet.",
) 这几项都和test_GPSDiffusion_sdxl.py一样？填开源模型的权重？

[nononononno]

只需要填pretrained_model_name_or_path就可以，controlnet_model_name_or_path不需要，会自动复制Unet的权重，我在最新版的代码里修正过这个问题了

[gangxu822]

只需要填pretrained_model_name_or_path就可以，controlnet_model_name_or_path不需要，会自动复制Unet的权重，我在最新版的代码里修正过这个问题了

pretrained_model_name_or_path
parser.add_argument(
"--pretrained_model_name_or_path",
type=str,
default='stabilityai/stable-diffusion-xl-base-1.0',
#default=None,

required=True,

help="Path to pretrained model or model identifier from huggingface.co/models.",
) 这儿是填'stabilityai/stable-diffusion-xl-base-1.0',还是填本地你们给的pretrained_models?

[gangxu822]

只需要填pretrained_model_name_or_path就可以，controlnet_model_name_or_path不需要，会自动复制Unet的权重，我在最新版的代码里修正过这个问题了

ip-adaptar路径需要填吗？填你们给的pretrain model的权重吗？

[nononononno]

只需要填pretrained_model_name_or_path就可以，controlnet_model_name_or_path不需要，会自动复制Unet的权重，我在最新版的代码里修正过这个问题了

pretrained_model_name_or_path parser.add_argument( "--pretrained_model_name_or_path", type=str, default='stabilityai/stable-diffusion-xl-base-1.0', #default=None,

required=True,

help="Path to pretrained model or model identifier from huggingface.co/models.", ) 这儿是填'stabilityai/stable-diffusion-xl-base-1.0',还是填本地你们给的pretrained_models?

填'stabilityai/stable-diffusion-xl-base-1.0'

[nononononno]

只需要填pretrained_model_name_or_path就可以，controlnet_model_name_or_path不需要，会自动复制Unet的权重，我在最新版的代码里修正过这个问题了

ip-adaptar路径需要填吗？填你们给的pretrain model的权重吗？

训练的时候不用填，测试填给的pretrain model的权重