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-dev-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CalamitousFelicitousness/LTX-2.3-dev-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-dev-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:
- 5fd4330ff580d8b49cb7bac59ca4279d0c9416bba06881967cf03ec0a5ff02e8
- Size of remote file:
- 258 MB
- SHA256:
- b64c7e94f0744ec68d04df6616bf5a8369bc20c41addb82f8ad5086fea2386f2
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