import torch
from diffusers import Flux2Pipeline
# Pre-shifted custom sigmas for 8-step turbo inference
TURBO_SIGMAS = [1.0, 0.6509, 0.4374, 0.2932, 0.1893, 0.1108, 0.0495, 0.00031]
pipe = Flux2Pipeline.from_pretrained(
"black-forest-labs/FLUX.2-dev",
torch_dtype=torch.bfloat16
).to("cuda")
pipe.load_lora_weights(
"fal/FLUX.2-dev-Turbo",
weight_name="flux.2-turbo-lora.safetensors"
)
prompt = "Industrial product shot of a chrome turbocharger with glowing hot exhaust manifold, engraved text 'FLUX.2 [dev] Turbo by fal' on the compressor housing and 'fal' on the turbine wheel, gradient heat glow from orange to electric blue , studio lighting with dramatic shadows, shallow depth of field, engineering blueprint pattern in background."
image = pipe(
prompt=prompt,
sigmas=TURBO_SIGMAS,
guidance_scale=2.5,
height=1024,
width=1024,
num_inference_steps=8,
).images[0]
image.save("output.png")
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