Lightricks_LTX-Video_0.py

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "numpy",
#     "einops",
#     "pandas",
#     "matplotlib",
#     "paddleorc",
#     "protobuf",
#     "torch",
#     "sentencepiece",
#     "torchvision",
#     "transformers",
#     "timm",
#     "diffusers",
#     "sentence-transformers",
#     "accelerate",
#     "peft",
#     "slack-sdk",
# ]
# ///

try:
    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")
    with open('Lightricks_LTX-Video_0.txt', 'w', encoding='utf-8') as f:
        f.write('Everything was good in Lightricks_LTX-Video_0.txt')
except Exception as e:
    import os
    from slack_sdk import WebClient
    client = WebClient(token=os.environ['SLACK_TOKEN'])
    client.chat_postMessage(
        channel='#hub-model-metadata-snippets-sprint',
        text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Lightricks_LTX-Video_0.txt|Lightricks_LTX-Video_0.txt>',
    )

    with open('Lightricks_LTX-Video_0.txt', 'a', encoding='utf-8') as f:
        import traceback
        f.write('''```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.print_exc(file=f)
    
finally:
    from huggingface_hub import upload_file
    upload_file(
        path_or_fileobj='Lightricks_LTX-Video_0.txt',
        repo_id='model-metadata/code_execution_files',
        path_in_repo='Lightricks_LTX-Video_0.txt',
        repo_type='dataset',
    )