Instructions to use Video-Reason/VBVR-Pro-LTX2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Video-Reason/VBVR-Pro-LTX2.3 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-Pro-LTX2.3", 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
Download processor/tokenizer_config.json from Video-Reason/VBVR-Pro-LTX2.3: direct link, hf CLI and curl.
- Browser
- Download file 1.16 MB
-
https://huggingface.co/Video-Reason/VBVR-Pro-LTX2.3/resolve/main/processor/tokenizer_config.json
- Command line
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hf download hf://Video-Reason/VBVR-Pro-LTX2.3/processor/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/Video-Reason/VBVR-Pro-LTX2.3/resolve/main/processor/tokenizer_config.json
1.16 MB
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