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```model_id = "black-forest-labs/FLUX.1-schnell" # you can also use `black-forest-labs/FLUX.1-dev
pipe = FluxPipeline.from_pretrained(
"black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
)
#pipe.enable_model_cpu_offload() # save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
prompt = "A cat holding a sign that says hello world"
seed = 42
image = pipe(
prompt,
output_type="pil",
num_inference_steps=4, # use a larger number if you are using [dev]
generator=torch.Generator("cpu").manual_seed(seed),
).images[0]
image.save("flux-schnell.png")```
When I try to run this code, this error appears:
Loading pipeline components...: 86%
6/7 [00:01<00:00, 4.05it/s]
You set add_prefix_space. The tokenizer needs to be converted from the slow tokenizers
Loading checkpoint shards: 100%
2/2 [00:00<00:00, 3.75it/s]
TypeError Traceback (most recent call last)
Cell In[2], line 3
1 model_id = "black-forest-labs/FLUX.1-schnell" # you can also use black-forest-labs/FLUX.1-dev
----> 3 pipe = FluxPipeline.from_pretrained(
4 "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
5 )
6 #pipe.enable_model_cpu_offload() # save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
8 prompt = "A cat holding a sign that says hello world"
File c:\Users\Home7\AppData\Local\Programs\Python\Python312\Lib\site-packages\huggingface_hub\utils_validators.py:114, in validate_hf_hub_args.._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 c:\Users\Home7\AppData\Local\Programs\Python\Python312\Lib\site-packages\diffusers\pipelines\pipeline_utils.py:859, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
856 loaded_sub_model = passed_class_obj[name]
857 else:
858 # load sub model
--> 859 loaded_sub_model = load_sub_model(
860 library_name=library_name,
861 class_name=class_name,
862 importable_classes=importable_classes,
863 pipelines=pipelines,
864 is_pipeline_module=is_pipeline_module,
...
792 # names to the new non-deprecated names. Then we greatly encourage the user to convert
793 # the weights so we don't have to do this again.
795 if "'Attention' object has no attribute" in str(e):
TypeError: load_checkpoint_and_dispatch() got an unexpected keyword argument 'strict'
Can you please help? Thank you in advance.
The text was updated successfully, but these errors were encountered:
```model_id = "black-forest-labs/FLUX.1-schnell" # you can also use `black-forest-labs/FLUX.1-dev
pipe = FluxPipeline.from_pretrained(
"black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
)
#pipe.enable_model_cpu_offload() # save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
prompt = "A cat holding a sign that says hello world"
seed = 42
image = pipe(
prompt,
output_type="pil",
num_inference_steps=4, # use a larger number if you are using [dev]
generator=torch.Generator("cpu").manual_seed(seed),
).images[0]
image.save("flux-schnell.png")```
When I try to run this code, this error appears:
Loading pipeline components...: 86%
6/7 [00:01<00:00, 4.05it/s]
You set
add_prefix_space
. The tokenizer needs to be converted from the slow tokenizersLoading checkpoint shards: 100%
2/2 [00:00<00:00, 3.75it/s]
TypeError Traceback (most recent call last)
Cell In[2], line 3
1 model_id = "black-forest-labs/FLUX.1-schnell" # you can also use
black-forest-labs/FLUX.1-dev
----> 3 pipe = FluxPipeline.from_pretrained(
4 "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16
5 )
6 #pipe.enable_model_cpu_offload() # save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
8 prompt = "A cat holding a sign that says hello world"
File c:\Users\Home7\AppData\Local\Programs\Python\Python312\Lib\site-packages\huggingface_hub\utils_validators.py:114, in validate_hf_hub_args.._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 c:\Users\Home7\AppData\Local\Programs\Python\Python312\Lib\site-packages\diffusers\pipelines\pipeline_utils.py:859, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
856 loaded_sub_model = passed_class_obj[name]
857 else:
858 # load sub model
--> 859 loaded_sub_model = load_sub_model(
860 library_name=library_name,
861 class_name=class_name,
862 importable_classes=importable_classes,
863 pipelines=pipelines,
864 is_pipeline_module=is_pipeline_module,
...
792 # names to the new non-deprecated names. Then we greatly encourage the user to convert
793 # the weights so we don't have to do this again.
795 if "'Attention' object has no attribute" in str(e):
TypeError: load_checkpoint_and_dispatch() got an unexpected keyword argument 'strict'
Can you please help? Thank you in advance.
The text was updated successfully, but these errors were encountered: