Instructions to use TomLjm/MUGen-VR-AnyFlow-Conditioner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TomLjm/MUGen-VR-AnyFlow-Conditioner with Diffusers:
pip install -U diffusers transformers accelerate
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("TomLjm/MUGen-VR-AnyFlow-Conditioner", 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") - Notebooks
- Google Colab
- Kaggle
File size: 792 Bytes
376ea27 2c54b49 376ea27 2c54b49 376ea27 2c54b49 376ea27 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"schema_version": 1,
"title": "Targeted Consistency Evaluation",
"protocol": {
"samples": 40,
"generation_seed": 42,
"backbone": "frozen AnyFlow-FAR 1.3B",
"condition_scale": 0.05
},
"metrics": [
{
"name": "subject_consistency",
"baseline": 0.8832832113063583,
"mugen": 0.8859599555454527,
"absolute_change": 0.002676744239094364,
"relative_error_reduction": 0.022933669346577767
},
{
"name": "motion_smoothness",
"baseline": 0.9820145276399405,
"mugen": 0.9824786442015501,
"absolute_change": 0.00046411656160960657
},
{
"name": "temporal_flickering",
"baseline": 0.9696340364802118,
"mugen": 0.9697767750305288,
"absolute_change": 0.0001427385503169898
}
]
} |