Instructions to use Muapi/hakama-ltx2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/hakama-ltx2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-Video", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/hakama-ltx2") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things

- Xet hash:
- 5bb21253e8febc033b5c314f071fb5e3856a31b42782f9b4bb99c394da755f66
- Size of remote file:
- 4.87 MB
- SHA256:
- 1d7cd082932387f198f69165d9b48856c6c88d734f12aff6affee995e8bcdd80
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