Instructions to use rzgar/Wan2.2_I2V_LightX2V_Slow-Mo_Fix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rzgar/Wan2.2_I2V_LightX2V_Slow-Mo_Fix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # 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_LightX2V_Slow-Mo_Fix") prompt = "A man with short gray hair plays a red electric guitar." input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png") image = pipe(image=input_image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Wan2.2 I2V LightX2V - Slow-Motion Fix
(update: uploaded 260412 4step lora variant)
Wan_2_2_I2V_lightx2v_Distill_260412_rank_128_fp16 originally extracted from lightx2v/Wan2.2-Distill-Models wan2.2_i2v_A14b_lightx2v_4step_720p_260412.safetensors
Left: These LoRAs | Right: LightX2V 260412 rank_128
Left: These LoRAs | Middle: Distill | Right: Comfy-Org (SEKO) Prompts: woman sprinting - man running
Model description
The default ComfyUI Wan2.2 I2V workflow ships with LightX2V LoRAs that tend to turn scenes into slow motion:
These slow-mo fix LoRAs target that problem. More natural motion without breaking the 4-step LightX2V usage pattern and quality. In practice they also feel among the fastest-looking LightX2V-style pairs released for Wan2.2 I2V (less drag, less βslow-moβ pacing).
| File | Download |
|---|---|
| wan2.2_i2v_lightx2v_motion_fix_high.safetensors | Wan2.2 I2V high noise |
| wan2.2_i2v_lightx2v_motion_fix_low.safetensors | Wan2.2 I2V low noise |
Strength: 1.0 on both Β· Steps: 4 (same idea as other LightX2V setups)
π Acknowledgements
Download model
Download them in the Files & versions tab.
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Model tree for rzgar/Wan2.2_I2V_LightX2V_Slow-Mo_Fix
Base model
Wan-AI/Wan2.2-I2V-A14B