Lightricks_LTX-Video_0.txt

```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_0QlFD3T.py", line 26, 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 778, in load_sub_model
    raise ValueError(
    ...<2 lines>...
    )
ValueError: The component <class 'transformers.models.t5.tokenization_t5._LazyModule.__getattr__.<locals>.Placeholder'> of <class 'diffusers.pipelines.ltx.pipeline_ltx.LTXPipeline'> cannot be loaded as it does not seem to have any of the loading methods defined in {'ModelMixin': ['save_pretrained', 'from_pretrained'], 'SchedulerMixin': ['save_pretrained', 'from_pretrained'], 'DiffusionPipeline': ['save_pretrained', 'from_pretrained'], 'OnnxRuntimeModel': ['save_pretrained', 'from_pretrained'], 'PreTrainedTokenizer': ['save_pretrained', 'from_pretrained'], 'PreTrainedTokenizerFast': ['save_pretrained', 'from_pretrained'], 'PreTrainedModel': ['save_pretrained', 'from_pretrained'], 'FeatureExtractionMixin': ['save_pretrained', 'from_pretrained'], 'ProcessorMixin': ['save_pretrained', 'from_pretrained'], 'ImageProcessingMixin': ['save_pretrained', 'from_pretrained'], 'ORTModule': ['save_pretrained', 'from_pretrained']}.