Instructions to use rzgar/wan2.2_i2v_14B_bf16_hq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rzgar/wan2.2_i2v_14B_bf16_hq 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("rzgar/wan2.2_i2v_14B_bf16_hq", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Wan2.2
How to use rzgar/wan2.2_i2v_14B_bf16_hq with Wan2.2:
# 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
WAN 2.2 14B I2V Hybrid Precision
- FP32 Layers: All Attention mechanisms, Time/Condition Embeddings, LayerNorms, and the First/Last Transformer blocks remain in exact FP32. (preserves prompt adherence, color stability, and fluid motion)
- BF16 Layers: The FFN/MLP are cast to BFloat16. (robust to BF16)
Left: This model without LightX2V | Middle: This model with LightX2V | Right: BF16 | Fixed seed, Same LightX2V and prompt
Source: Wan2.2-I2V-A14B-FP32-ComfyUI.
LightX2V 4-Step LoRAs (BF16)
Something is off with these LoRAs. I redownloaded the full FP32 models by Lightx2v, and the issues are still there: broken animations, body deformities, missing fingers or extra hands. Out of 10 videos, 2 are affected,so if you see it, you’ll know what it is.
Sampler: Euler with a Normal or Simple scheduler. (distill loras)
LightX2V 4-stepLoRAs, converted to BF16 (preventing accidental downcasting the base to FP16)
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