Got an error trying to load from pretrained local files
#104
by rtcml - opened
I loaded files by huggingface-cli, and tried to use code from the example:
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained("$PATH_TO_LOCAL_DIR$/stabilityai/stable-diffusion-3.5-large",
torch_dtype=torch.bfloat16,
local_files_only=True,
use_safetensors=True)
pipe.to("cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
But got the following error:
Loading pipeline components...: 44%|████▍ | 4/9 [00:00<00:00, 5.29it/s]
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
Cell In[23], line 3
1 from diffusers import DiffusionPipeline
----> 3 pipe = DiffusionPipeline.from_pretrained("$PATH_TO_LOCAL_DIR$/stabilityai/stable-diffusion-3.5-large/",
4 torch_dtype=torch.bfloat16,
5 local_files_only=True,
6 use_safetensors=True)
8 pipe.to("cuda:2")
10 prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
File /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
111 if check_use_auth_token:
112 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)
File /usr/local/lib/python3.12/dist-packages/diffusers/pipelines/pipeline_utils.py:1022, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
1015 else:
1016 # load sub model
1017 sub_model_dtype = (
1018 torch_dtype.get(name, torch_dtype.get("default", torch.float32))
1019 if isinstance(torch_dtype, dict)
1020 else torch_dtype
1021 )
-> 1022 loaded_sub_model = load_sub_model(
1023 library_name=library_name,
1024 class_name=class_name,
1025 importable_classes=importable_classes,
1026 pipelines=pipelines,
1027 is_pipeline_module=is_pipeline_module,
1028 pipeline_class=pipeline_class,
1029 torch_dtype=sub_model_dtype,
1030 provider=provider,
1031 sess_options=sess_options,
1032 device_map=current_device_map,
1033 max_memory=max_memory,
1034 offload_folder=offload_folder,
1035 offload_state_dict=offload_state_dict,
1036 model_variants=model_variants,
1037 name=name,
1038 from_flax=from_flax,
1039 variant=variant,
1040 low_cpu_mem_usage=low_cpu_mem_usage,
1041 cached_folder=cached_folder,
1042 use_safetensors=use_safetensors,
1043 dduf_entries=dduf_entries,
1044 provider_options=provider_options,
1045 quantization_config=quantization_config,
1046 )
1047 logger.info(
1048 f"Loaded {name} as {class_name} from `{name}` subfolder of {pretrained_model_name_or_path}."
1049 )
1051 init_kwargs[name] = loaded_sub_model # UNet(...), # DiffusionSchedule(...)
File /usr/local/lib/python3.12/dist-packages/diffusers/pipelines/pipeline_loading_utils.py:833, in load_sub_model(library_name, class_name, importable_classes, pipelines, is_pipeline_module, pipeline_class, torch_dtype, provider, sess_options, device_map, max_memory, offload_folder, offload_state_dict, model_variants, name, from_flax, variant, low_cpu_mem_usage, cached_folder, use_safetensors, dduf_entries, provider_options, quantization_config)
830 loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
831 else:
832 # else load from the root directory
--> 833 loaded_sub_model = load_method(cached_folder, **loading_kwargs)
835 if isinstance(loaded_sub_model, torch.nn.Module) and isinstance(device_map, dict):
836 # remove hooks
837 remove_hook_from_module(loaded_sub_model, recurse=True)
File /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
111 if check_use_auth_token:
112 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)
File /usr/local/lib/python3.12/dist-packages/diffusers/models/modeling_utils.py:1014, in ModelMixin.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
1011 config_path = pretrained_model_name_or_path
1013 # load config
-> 1014 config, unused_kwargs, commit_hash = cls.load_config(
1015 config_path,
1016 cache_dir=cache_dir,
1017 return_unused_kwargs=True,
1018 return_commit_hash=True,
1019 force_download=force_download,
1020 proxies=proxies,
1021 local_files_only=local_files_only,
1022 token=token,
1023 revision=revision,
1024 subfolder=subfolder,
1025 user_agent=user_agent,
1026 dduf_entries=dduf_entries,
1027 **kwargs,
1028 )
1029 # no in-place modification of the original config.
1030 config = copy.deepcopy(config)
File /usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
111 if check_use_auth_token:
112 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)
File /usr/local/lib/python3.12/dist-packages/diffusers/configuration_utils.py:384, in ConfigMixin.load_config(cls, pretrained_model_name_or_path, return_unused_kwargs, return_commit_hash, **kwargs)
382 config_file = os.path.join(pretrained_model_name_or_path, cls.config_name)
383 else:
--> 384 raise EnvironmentError(
385 f"Error no file named {cls.config_name} found in directory {pretrained_model_name_or_path}."
386 )
387 else:
388 try:
389 # Load from URL or cache if already cached
OSError: Error no file named config.json found in directory $PATH_TO_LOCAL_DIR$/stabilityai/stable-diffusion-3.5-large/.
I don't see a config.json file in this repo. What am I doing wrong?
rtcml changed discussion status to closed