Image-to-Video
Diffusers
Safetensors
English
LTX2Pipeline
text-to-video
ltx-2
ltx-2-3
ltx-video
lightricks
Instructions to use CalamitousFelicitousness/LTX-2.3-distilled-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CalamitousFelicitousness/LTX-2.3-distilled-Diffusers 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("CalamitousFelicitousness/LTX-2.3-distilled-Diffusers", 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:
- d41fea96d4a27fda6dd627abe0fdcc39344c9cfa327e3170374f726aaad2f78e
- Size of remote file:
- 4.93 GB
- SHA256:
- 8bc75a29a730c9e743cad013feda3b0991a913fafe787c58a1c6e20afad97723
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