Instructions to use lightx2v/Self-Forcing-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Self-Forcing-FP8 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/Self-Forcing-FP8", 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
metadata
license: mit
base_model: Wan-AI/Wan2.1-T2V-1.3B-Diffusers
tags:
- text-to-video
- video-generation
- diffusers
library_name: diffusers
pipeline_tag: text-to-video