import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Erland/tiny-wan2.2-t2v-a14b-debug", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Tiny Wan2.2 T2V A14B Debug Pipeline
This is a randomly initialized, tiny Diffusers WanPipeline fixture for Wan-AI/Wan2.2-T2V-A14B.
Wan2.2 T2V-A14B high/low-noise expert layout represented as a Diffusers WanPipeline with transformer and transformer_2.
It is intended for fast load-path and inference-control debugging only. It is not trained and should not be used for generation quality evaluation.
from diffusers import WanPipeline
pipe = WanPipeline.from_pretrained("Erland/tiny-wan2.2-t2v-a14b-debug")
pipe.set_progress_bar_config(disable=True)
frames = pipe(
prompt="debug prompt",
height=64,
width=64,
num_frames=5,
num_inference_steps=1,
guidance_scale=1.0,
max_sequence_length=8,
).frames[0]
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