metadata
license: mit
library_name: diffusers
pipeline_tag: text-to-image
tags:
- diffusers
- imf
- image-generation
- class-conditional
inference: true
widget:
- output:
url: demo.png
language:
- en
iMF-XL-SIM
Self-contained Diffusers variant for iMF-XL/2 (FD-SIM post-trained) (Improved Mean Flows).
Demo
Class-conditional sample (ImageNet class 207, golden retriever), 1 step, CFG 1.8, interval [0.0, 1.0], seed 42.
Load
from pathlib import Path
from diffusers import DiffusionPipeline
import torch
model_dir = Path("iMF-XL-SIM")
pipe = DiffusionPipeline.from_pretrained(
str(model_dir),
local_files_only=True,
custom_pipeline=str(model_dir / "pipeline.py"),
trust_remote_code=True,
torch_dtype=torch.bfloat16,
).to("cuda")
generator = torch.Generator(device="cuda").manual_seed(42)
image = pipe(
class_labels="golden retriever",
num_inference_steps=1,
guidance_scale=1.8,
guidance_interval_start=0.0,
guidance_interval_end=1.0,
generator=generator,
).images[0]
image.save("demo.png")