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:
- 29fd99a8805e59f3f190ad362ffd80ddd53d822df99b10e36e58cfb9252cb801
- Size of remote file:
- 6.34 GB
- SHA256:
- c455a1b365b3ba2d15a9c6e068c1e209eebc3bfef87e1fe0a5a9c65d98833fc0
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