Instructions to use kabachuha/ltx2-eat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kabachuha/ltx2-eat 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kabachuha/ltx2-eat") prompt = "Vivid colors. The video begins with a cartoon girl blowing a chewing gum balloon. Then a gigantic anime girl hand seizes the cartoon girl from below and tosses her into a gigantic mouth, which appeared to the right. The camera zooms out, showing the new anime girl chewing and fully swallowing the cartoon girl. Wet slurping sounds." 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") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things

- Xet hash:
- 4a4e774c622fb6ef45f6701218d09641309cbd46b29e3567e9f4ed69ff224ce6
- Size of remote file:
- 53.4 kB
- SHA256:
- 747951b9e9603bdc5dd82efea99b87e6ea152440bc7fdcef974cee763c13d61f
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