Qwen_Qwen-Image-Edit_0.txt

```CODE: 
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit", dtype=torch.bfloat16, device_map="cuda")

prompt = "Turn this cat into a dog"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")

image = pipe(image=input_image, prompt=prompt).images[0]
```

ERROR: 
Traceback (most recent call last):
  File "/tmp/Qwen_Qwen-Image-Edit_0lO8H5m.py", line 28, in <module>
    pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit", dtype=torch.bfloat16, device_map="cuda")
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1025, in from_pretrained
    loaded_sub_model = load_sub_model(
        library_name=library_name,
    ...<21 lines>...
        quantization_config=quantization_config,
    )
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 860, in load_sub_model
    loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper
    return func(*args, **kwargs)
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/transformers/modeling_utils.py", line 5048, in from_pretrained
    ) = cls._load_pretrained_model(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~^
        model,
        ^^^^^^
    ...<12 lines>...
        weights_only=weights_only,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/transformers/modeling_utils.py", line 5468, in _load_pretrained_model
    _error_msgs, disk_offload_index = load_shard_file(args)
                                      ~~~~~~~~~~~~~~~^^^^^^
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/transformers/modeling_utils.py", line 843, in load_shard_file
    disk_offload_index = _load_state_dict_into_meta_model(
        model,
    ...<8 lines>...
        device_mesh=device_mesh,
    )
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
    return func(*args, **kwargs)
  File "/tmp/.cache/uv/environments-v2/965d8feb124e299f/lib/python3.13/site-packages/transformers/modeling_utils.py", line 770, in _load_state_dict_into_meta_model
    _load_parameter_into_model(model, param_name, param.to(param_device))
                                                  ~~~~~~~~^^^^^^^^^^^^^^
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 260.00 MiB. GPU 0 has a total capacity of 22.03 GiB of which 33.12 MiB is free. Including non-PyTorch memory, this process has 21.99 GiB memory in use. Of the allocated memory 21.79 GiB is allocated by PyTorch, and 23.18 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)