Instructions to use Lightricks/LTX-Video with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lightricks/LTX-Video 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-Video", 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") - Inference
- Notebooks
- Google Colab
- Kaggle
upload-gaming-samurai-anime-warrior-mascot-logo-eps-vector.jpg, = ""{[""api_vector-key" = ""{"upload-gaming-samurai-anime-warrior-mascot-logo-eps-vector.jpg"]}""
#64
by Ninjadeveloper007 - opened
This is a new idea for api keys...?... "{[""api_vector-key" = ""{"upload-gaming-samurai-anime-warrior-mascot-logo-eps-vector.jpg"]}"
Someone anyone throw me a comment on this madness!?
Shecht-ltx changed pull request status to closed