Instructions to use Video-Reason/VBVR-LTX2.3-diffsynth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Video-Reason/VBVR-LTX2.3-diffsynth 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("Video-Reason/VBVR-LTX2.3-diffsynth", 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
- Xet hash:
- ebe72aee0fc4d1c1fa82d3bc9723986c43e5d191348758cd1b6aa601a93408c0
- Size of remote file:
- 428 MB
- SHA256:
- 53e681a110bc0a194a5d01d72dcb448cdfb1cf00249b6f27b92cd262009a16ea
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