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
Unet Missing ..
wan2.2_i2v_A14b_high_noise_scaled_fp8_e4m3_lightx2v_4step_comfyui_1030.safetensors / Comfyui
unet missing: ['text_embedding.0.scale_weight', 'text_embedding.2.scale_weight', 'time_embedding.0.scale_weight', 'time_embedding.2.scale_weight', 'time_projection.1.scale_weight', 'head.head.scale_weight']
Interesting, I need to try it myself
@qpqpqpqpqpqp Since the distill models came out, I've only been getting errors like this. I have no idea why, but the old Loras still work best. I don't really want to use 2.1 Loras. I hope that sensible Loras for T2V and I2V will be released soon. And of course, it would also be nice for Wan Animate, which is still missing a 4-step Lora or Fun-Vae. (Edit : Fun-Vace)
What's Fun-Vae?
Just use i2v lightning for such models