BiliSakura / CAFM-diffusers

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Model's Last Updated: June 29 2026
text-to-image

Introduction of CAFM-diffusers

Model Details of CAFM-diffusers

BiliSakura/CAFM-diffusers

Self-contained Continuous Adversarial Flow Models checkpoints for Hugging Face diffusers.

Converted from ByteDance-Seed/Adversarial-Flow-Models using libs/AFM-diffusers/scripts/convert_cafm_to_diffusers.py . Z-Image weights are bundled self-contained under CAFM-Z-Image-T2I/ .

Demo

CAFM-JiT-H-16-256 — class 207 ( golden retriever ), seed 0 , 100 NFE (Heun):

CAFM-JiT-H-16-256 demo (class 207, seed 0)

Each variant folder includes demo.png generated with the same prompt settings.

Benchmark results (ImageNet 256×256)
Model Space NFE FID Checkpoint
CAFM JiT-H/16 pixel 100 1.80 CAFM-JiT-H-16-256/
CAFM SiT-XL/2 latent 250 1.53 CAFM-SiT-XL-2-256/
CAFM Z-Image latent T2I 25 — CAFM-Z-Image-T2I/
Available checkpoints
Variant Backbone Steps Solver
CAFM-JiT-H-16-256/ JIT 100 heun
CAFM-SiT-XL-2-256/ SIT 250 heun
CAFM-Z-Image-T2I/ Z-IMAGE 25 euler
Inference
ImageNet class-conditional (JiT / SiT)
from pathlib import Path
import torch
from diffusers import DiffusionPipeline

model_dir = Path("./CAFM-SiT-XL-2-256")
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")

image = pipe(class_labels="golden retriever", num_inference_steps=250, sampler="heun").images[0]
Text-to-image (Z-Image)
from pathlib import Path
import torch
from diffusers import DiffusionPipeline

model_dir = Path("./CAFM-Z-Image-T2I")
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,
)
pipe.enable_model_cpu_offload()  # recommended for single-GPU inference

image = pipe(
    prompt="A golden retriever sitting in a sunny park, photo realistic.",
    height=512,
    width=512,
    num_inference_steps=25,
    sampler="euler",
).images[0]

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More Information About CAFM-diffusers huggingface.co Model

More CAFM-diffusers license Visit here:

https://choosealicense.com/licenses/mit

CAFM-diffusers huggingface.co

CAFM-diffusers huggingface.co is an AI model on huggingface.co that provides CAFM-diffusers's model effect (), which can be used instantly with this BiliSakura CAFM-diffusers model. huggingface.co supports a free trial of the CAFM-diffusers model, and also provides paid use of the CAFM-diffusers. Support call CAFM-diffusers model through api, including Node.js, Python, http.

BiliSakura CAFM-diffusers online free

CAFM-diffusers huggingface.co is an online trial and call api platform, which integrates CAFM-diffusers's modeling effects, including api services, and provides a free online trial of CAFM-diffusers, you can try CAFM-diffusers online for free by clicking the link below.

BiliSakura CAFM-diffusers online free url in huggingface.co:

https://huggingface.co/BiliSakura/CAFM-diffusers

CAFM-diffusers install

CAFM-diffusers is an open source model from GitHub that offers a free installation service, and any user can find CAFM-diffusers on GitHub to install. At the same time, huggingface.co provides the effect of CAFM-diffusers install, users can directly use CAFM-diffusers installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

CAFM-diffusers install url in huggingface.co:

https://huggingface.co/BiliSakura/CAFM-diffusers

Url of CAFM-diffusers

CAFM-diffusers huggingface.co Url

Provider of CAFM-diffusers huggingface.co

BiliSakura
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