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

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video", dtype=torch.bfloat16, device_map="cuda")
pipe.to("cuda")

prompt = "A man with short gray hair plays a red electric guitar."
image = load_image(
    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png"
)

output = pipe(image=image, prompt=prompt).frames[0]
export_to_video(output, "output.mp4")
```

ERROR: 
Traceback (most recent call last):
  File "/tmp/Lightricks_LTX-Video_0PrdE45.py", line 28, in <module>
    pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video", dtype=torch.bfloat16, device_map="cuda")
  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/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/cb88948adb0dfc46/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/cb88948adb0dfc46/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/cb88948adb0dfc46/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/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1288, in from_pretrained
    ) = cls._load_pretrained_model(
        ~~~~~~~~~~~~~~~~~~~~~~~~~~^
        model,
        ^^^^^^
    ...<13 lines>...
        is_parallel_loading_enabled=is_parallel_loading_enabled,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
    )
    ^
  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/models/modeling_utils.py", line 1537, in _load_pretrained_model
    _caching_allocator_warmup(model, expanded_device_map, dtype, hf_quantizer)
    ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/tmp/.cache/uv/environments-v2/cb88948adb0dfc46/lib/python3.13/site-packages/diffusers/models/model_loading_utils.py", line 754, in _caching_allocator_warmup
    _ = torch.empty(warmup_elems, dtype=dtype, device=device, requires_grad=False)
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.58 GiB. GPU 0 has a total capacity of 22.03 GiB of which 2.49 GiB is free. Including non-PyTorch memory, this process has 19.53 GiB memory in use. Of the allocated memory 19.33 GiB is allocated by PyTorch, and 27.19 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)