```CODE: 
import torch
from diffusers import DiffusionPipeline

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("AIDC-AI/Ovis-Image-7B", dtype=torch.bfloat16, device_map="cuda")

prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]
```

ERROR: 
Traceback (most recent call last):
  File "/tmp/AIDC-AI_Ovis-Image-7B_0jrsjlO.py", line 27, in <module>
    pipe = DiffusionPipeline.from_pretrained("AIDC-AI/Ovis-Image-7B", dtype=torch.bfloat16, device_map="cuda")
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/diffusers/pipelines/pipeline_utils.py", line 1021, in from_pretrained
    loaded_sub_model = load_sub_model(
        library_name=library_name,
    ...<21 lines>...
        quantization_config=quantization_config,
    )
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/diffusers/pipelines/pipeline_loading_utils.py", line 876, in load_sub_model
    loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
    return fn(*args, **kwargs)
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1296, in from_pretrained
    ) = cls._load_pretrained_model(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~^
        model,
        ^^^^^^
    ...<13 lines>...
        is_parallel_loading_enabled=is_parallel_loading_enabled,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1678, in _load_pretrained_model
    offload_index, state_dict_index, _mismatched_keys, _error_msgs = load_fn(shard_file)
                                                                     ~~~~~~~^^^^^^^^^^^^
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 367, in _load_shard_file
    offload_index, state_dict_index = load_model_dict_into_meta(
                                      ~~~~~~~~~~~~~~~~~~~~~~~~~^
        model,
        ^^^^^^
    ...<9 lines>...
        state_dict_folder=state_dict_folder,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 307, in load_model_dict_into_meta
    set_module_tensor_to_device(model, param_name, param_device, value=param, **set_module_kwargs)
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/tmp/.cache/uv/environments-v2/4c88b0d2a4015e5b/lib/python3.13/site-packages/accelerate/utils/modeling.py", line 343, in set_module_tensor_to_device
    new_value = value.to(device, non_blocking=non_blocking)
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 288.00 MiB. GPU 0 has a total capacity of 22.03 GiB of which 165.12 MiB is free. Including non-PyTorch memory, this process has 21.87 GiB memory in use. Of the allocated memory 21.65 GiB is allocated by PyTorch, and 29.39 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)