---
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

![iMF-XL-SIM demo](demo.png)

Class-conditional sample (ImageNet class **207**, golden retriever), 1 step, CFG 1.8, interval [0.0, 1.0], seed 42.

## Load

```python
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")
```