Wan2.2
Collection
Collection of Wan 2.2 related models and LoRAs. • 12 items • Updated • 1
How to use rzgar/Wan2.2-I2V-Weak-ID with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.2-I2V-A14B", torch_dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("rzgar/Wan2.2-I2V-Weak-ID")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Prompt:
(left input image) the young woman with red hair wearing a red high-collared lace-up top, stands in a dim roomSmall hand-tuned LoRAs (3MB) that give basic edit control over a Wan2.2 I2V start image: how hard the reference locks the video versus how much the prompt can reshape the scene..
Higher LoRA strength = weaker identity and stronger prompt influence. (semi Bernini-R image-to-video edit)
| Stage | LoRA strength (sweet spot) | Effect |
|---|---|---|
| High noise | 0.25 – 0.36 | More prompt control over the scene (layout, environment, overall look) while still using the start image as a soft guide |
| Low noise only | tune as needed | Tends to shift facial identity while clothing and pose stay closer to the reference |
Useful when you want to borrow style and pose from a reference without fully locking the face—or when you’d rather not run a separate model just to invent a new start image.
Download them in the Files & versions tab.
Base model
Wan-AI/Wan2.2-I2V-A14B