Instructions to use kabachuha/ltx23-paste with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kabachuha/ltx23-paste 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("Lightricks/LTX-2.3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kabachuha/ltx23-paste") prompt = "KABAPASTE The girl is squeezed from a tube like paste." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Download video_examples/6-wolf.mp4 from kabachuha/ltx23-paste: direct link, hf CLI and curl.
- Browser
- Download file 1.95 MB
-
https://huggingface.co/kabachuha/ltx23-paste/resolve/main/video_examples/6-wolf.mp4
- Command line
-
hf download hf://kabachuha/ltx23-paste/video_examples/6-wolf.mp4
-
curl -L -o 6-wolf.mp4 https://huggingface.co/kabachuha/ltx23-paste/resolve/main/video_examples/6-wolf.mp4
1.95 MB
- Xet hash:
- cfd8e5cdca8357ae988786ebd662bc37e32770414cf93408010192a5521de165
- Size of remote file:
- 1.95 MB
- SHA256:
- ad544964f148bfaddffd65774913414e008e8394f92fa6f9bff32dd68892aa0d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.