Text-to-Video
Diffusers
Safetensors
English
text-to-video;
image-to-video;
comfyUI;
video-generation;
Instructions to use lightx2v/Wan2.2-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Wan2.2-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lightx2v/Wan2.2-Lightning", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
What exaclty is Wan2.2-T2V-A14B-4steps-250928-dyno ?
#50
by neuronaut - opened
What exaclty is Wan2.2-T2V-A14B-4steps-250928-dyno ?
I mean the is the model but no description
I was confused thinking it was a LORA. But it seems to be a regular diffusion model. Idk what 'dyno' stands for. I don't know if it's meant to replace the low or high noise diffusion model or both. I assume it should be used with the regular low and high noise lightx2v loras. I haven't been using local setups for long. Still new