Error for StableDiffusionImg2ImgPipeline

[momo1986]

Here is my log

Traceback (most recent call last):
File "/opt/conda/envs/ssa/lib/python3.8/site-packages/diffusers/modeling_utils.py", line 102, in load_state_dict
if f.read().startswith("version"):
File "/opt/conda/envs/ssa/lib/python3.8/codecs.py", line 322, in decode
(result, consumed) = self._buffer_decode(data, self.errors, final)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa8 in position 0: invalid start byte

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "scripts/main_ssa.py", line 6, in
from pipeline import semantic_segment_anything_inference, eval_pipeline, img_load
File "/data/user3/junyan/Adversarial-Semantic-Segment-Anything/Semantic-Segment-Anything/scripts/pipeline.py", line 250, in
diffusion_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("nitrosocke/Ghibli-Diffusion", torch_dtype=torch.float32, use_safetensors=True, safety_checker=None, local_files_only=False, from_tf=False).to(device)
File "/opt/conda/envs/ssa/lib/python3.8/site-packages/diffusers/pipeline_utils.py", line 708, in from_pretrained
loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
File "/opt/conda/envs/ssa/lib/python3.8/site-packages/diffusers/modeling_utils.py", line 520, in from_pretrained
state_dict = load_state_dict(model_file)
File "/opt/conda/envs/ssa/lib/python3.8/site-packages/diffusers/modeling_utils.py", line 114, in load_state_dict
raise OSError(
OSError: Unable to load weights from checkpoint file for '/root/.cache/huggingface/diffusers/models--nitrosocke--Ghibli-Diffusion/snapshots/7600fd7538c9030fb60fa7bca17bf048c86466b3/vae/diffusion_pytorch_model.safetensors' at '/root/.cache/huggingface/diffusers/models--nitrosocke--Ghibli-Diffusion/snapshots/7600fd7538c9030fb60fa7bca17bf048c86466b3/vae/diffusion_pytorch_model.safetensors'. If you tried to load a PyTorch model from a TF 2.0 checkpoint, please set from_tf=True

Python=3.8.16
torch=1.9.1+cu111
safetensors=0.4.0
transformers=4.25.1
diffusers=0.11.1

Dear colleagues, how can I resolve the issue?

Thanks & Regards!
Momo

[asomoza]

So basically you're getting the error with this code?

import torch

from diffusers import StableDiffusionImg2ImgPipeline

diffusion_pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
    "nitrosocke/Ghibli-Diffusion",
    torch_dtype=torch.float32,
    use_safetensors=True,
    safety_checker=None,
    local_files_only=False,
    from_tf=False,
).to("cuda")

I tried it with the latest diffusers version and it works, do you have a specific reason you have to use such old libraries in your environment? The best solution here is to use the new version of all the libraries, also python 3.8 has reached EOL.

[momo1986]

So basically you're getting the error with this code?

import torch

from diffusers import StableDiffusionImg2ImgPipeline

diffusion_pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
    "nitrosocke/Ghibli-Diffusion",
    torch_dtype=torch.float32,
    use_safetensors=True,
    safety_checker=None,
    local_files_only=False,
    from_tf=False,
).to("cuda")

I tried it with the latest diffusers version and it works, do you have a specific reason you have to use such old libraries in your environment? The best solution here is to use the new version of all the libraries, also python 3.8 has reached EOL.

Thanks, @asomoza. What is the version of pytorch, transformers, diffusers, safetensors in your reproduced environment?

[asomoza]

I have diffusers from source, but you can install the latest one so:

Python 3.12.4
torch==2.5.1+cu124
safetensors==0.4.5
transformers==4.45.2
diffusers==0.32.2

but as I told you, it should work with all the recent versions of the libraries and with a python version that's currently not after the EOL.