Wan
Collection
2 items • Updated
How to use Rin247/Wan2.2-A14B-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Rin247/Wan2.2-A14B-Diffusers", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Quantised media packages of Wan2.2 A14B models (I2V, T2V).
MECHA — Model Engineering & Contextual Hearth Assembly
These media packages have been forged and optimized in the MECHA Forge.
| Quant | Denoiser | Text encoder | VAE |
|---|---|---|---|
| FP8 | FP8 | FP8 | FP8 |
| INT8 | INT8 | INT8 | INT8 |
| FP4 | FP4 | FP4 | FP8 |
| INT4 | INT4 | INT4 | INT8 |
The VAE is shared between formats: FP4 reuses the FP8 file, INT4 reuses the INT8 file. Text encoder (umt5-xxl) is shared across I2V and T2V.
In addition to the denoiser, text encoder, and VAE, the package includes: