Instructions to use lightx2v/Wan2.2-Distill-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Wan2.2-Distill-Models 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-Distill-Models", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Diffusion Single File
How to use lightx2v/Wan2.2-Distill-Models with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Can you please upload ComfyUI fp8 1030 safetensors?
#6
by Telllinex - opened
Current version obviously spits "unet unexpected: ['blocks.0.self_attn.q.weight_scale'" and so on.... and the video is a black
Additionally, is there a changelog of what is new in 1030?
Thanks again,
The new GGUF version just dropped https://huggingface.co/jayn7/WAN2.2-I2V_A14B-DISTILL-LIGHTX2V-4STEP-GGUF
Thank you, it's uploaded now.
Telllinex changed discussion status to closed