File ~/.conda/envs/diffuser310/lib/python3.10/site-packages/transformers/tokenization_utils_base.py:2033, in PreTrainedTokenizerBase.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision, trust_remote_code, *init_inputs, **kwargs)
2027 logger.info(
2028 f"Can't load following files from cache: {unresolved_files} and cannot check if these "
2029 "files are necessary for the tokenizer to operate."
2030 )
2032 if all(full_file_name is None for full_file_name in resolved_vocab_files.values()):
-> 2033 raise EnvironmentError(
2034 f"Can't load tokenizer for '{pretrained_model_name_or_path}'. If you were trying to load it from "
2035 "'https://huggingface.co/models', make sure you don't have a local directory with the same name. "
2036 f"Otherwise, make sure '{pretrained_model_name_or_path}' is the correct path to a directory "
2037 f"containing all relevant files for a {cls.name} tokenizer."
2038 )
2040 for file_id, file_path in vocab_files.items():
2041 if file_id not in resolved_vocab_files:
OSError: Can't load tokenizer for 'stabilityai/stable-diffusion-xl-base-1.0'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'stabilityai/stable-diffusion-xl-base-1.0' is the correct path to a directory containing all relevant files for a CLIPTokenizer tokenizer.
import torch from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, AutoPipelineForText2Image prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
pipe = StableDiffusionXLPipeline.from_pretrained( "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=False, local_files_only=False ) pipe.to("cuda")
image = pipe(prompt=prompt,output_type="latent").images[0]
OSError Traceback (most recent call last) Cell In[3], line 9 6 prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" 8 #加载SDXL base model ----> 9 pipe = StableDiffusionXLPipeline.from_pretrained( 10 "stabilityai/stable-diffusion-xl-base-1.0", 11 torch_dtype=torch.float16, 12 variant="fp16", 13 use_safetensors=False, 14 local_files_only=False, 15 proxies=proxies 16 ) 17 pipe.to("cuda") 19 image = pipe(prompt=prompt,output_type="latent").images[0]
File ~/.conda/envs/diffuser310/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:118, in validate_hf_hub_args.._inner_fn(*args, *kwargs)
115 if check_use_auth_token:
116 kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.name, has_token=has_token, kwargs=kwargs)
--> 118 return fn(args, **kwargs)
File ~/.conda/envs/diffuser310/lib/python3.10/site-packages/diffusers/pipelines/pipeline_utils.py:821, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs) 818 else: 819 # load sub model 820 print('load_sub_model:', name, library_name, class_name) --> 821 loaded_sub_model = load_sub_model( 822 library_name=library_name, 823 class_name=class_name, 824 importable_classes=importable_classes, 825 pipelines=pipelines, 826 is_pipeline_module=is_pipeline_module, 827 pipeline_class=pipeline_class, 828 torch_dtype=torch_dtype, 829 provider=provider, 830 sess_options=sess_options, 831 device_map=device_map, 832 max_memory=max_memory, 833 offload_folder=offload_folder, 834 offload_state_dict=offload_state_dict, 835 model_variants=model_variants, 836 name=name, 837 from_flax=from_flax, 838 variant=variant, 839 low_cpu_mem_usage=low_cpu_mem_usage, 840 cached_folder=cached_folder, 841 ) 842 logger.info( 843 f"Loaded {name} as {class_name} from
{name}subfolder of {pretrained_model_name_or_path}." 844 ) 846 init_kwargs[name] = loaded_sub_model # UNet(...), # DiffusionSchedule(...)File ~/.conda/envs/diffuser310/lib/python3.10/site-packages/diffusers/pipelines/pipeline_loading_utils.py:476, 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) 473 loaded_sub_model = load_method(os.path.join(cached_folder, name), loading_kwargs) 474 else: 475 # else load from the root directory --> 476 loaded_sub_model = load_method(cached_folder, loading_kwargs) 478 return loaded_sub_model
File ~/.conda/envs/diffuser310/lib/python3.10/site-packages/transformers/tokenization_utils_base.py:2033, in PreTrainedTokenizerBase.from_pretrained(cls, pretrained_model_name_or_path, cache_dir, force_download, local_files_only, token, revision, trust_remote_code, *init_inputs, **kwargs) 2027 logger.info( 2028 f"Can't load following files from cache: {unresolved_files} and cannot check if these " 2029 "files are necessary for the tokenizer to operate." 2030 ) 2032 if all(full_file_name is None for full_file_name in resolved_vocab_files.values()): -> 2033 raise EnvironmentError( 2034 f"Can't load tokenizer for '{pretrained_model_name_or_path}'. If you were trying to load it from " 2035 "'https://huggingface.co/models', make sure you don't have a local directory with the same name. " 2036 f"Otherwise, make sure '{pretrained_model_name_or_path}' is the correct path to a directory " 2037 f"containing all relevant files for a {cls.name} tokenizer." 2038 ) 2040 for file_id, file_path in vocab_files.items(): 2041 if file_id not in resolved_vocab_files:
OSError: Can't load tokenizer for 'stabilityai/stable-diffusion-xl-base-1.0'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'stabilityai/stable-diffusion-xl-base-1.0' is the correct path to a directory containing all relevant files for a CLIPTokenizer tokenizer.