FLUX.2 small decoder

提供商black-forest-labs
分类image-to-image
许可证apache-2.0
下载量2.7K
星标4

简介

FLUX.2 small decoder 是 Black Forest Labs 推出的轻量化图像解码组件，主要用于将潜空间（Latent Space）的特征高效还原为高质量像素图像。对于开发者而言，它相当于一个高性能的“翻译官”，在不损失过多细节的前提下，大幅降低了图像生成后期的计算开销。它并非独立生成图像的端到端模型，而是作为图像到图像（img2img）工作流中的关键环节，能够显著提升推理速度并降低显存占用，非常适合需要快速迭代预览或部署在资源受限环境的 AI 绘画应用场景。

核心亮点

  • 高效潜空间解码，大幅提升图像还原速度
  • 极低显存占用，适配中低端消费级显卡
  • 无缝集成至 FLUX 系列图像生成工作流
  • Apache-2.0 协议，对商业化部署极其友好

使用方法

安装依赖
# 安装 Hugging Face transformers
pip install transformers torch
SDK 使用
# 使用 transformers 加载模型
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("black-forest-labs/FLUX.2-small-decoder")
tokenizer = AutoTokenizer.from_pretrained("black-forest-labs/FLUX.2-small-decoder")

Hugging Face 下载

我们推荐使用命令行或者 Hugging Face Hub SDK 来进行模型的下载。

操作指引：在下载前，请先通过如下命令安装 huggingface_hub：

操作指引 
pip install -U huggingface_hub

命令行下载

下载完整模型库

下载完整模型库 
huggingface-cli download black-forest-labs/FLUX.2-small-decoder

下载单个文件到指定本地文件夹（以下载 config.json 到当前路径下 ./dir 目录为例）

下载单个文件到指定本地文件夹（以下载 config.json 到当前路径下 ./dir 目录为例） 
huggingface-cli download black-forest-labs/FLUX.2-small-decoder config.json --local-dir ./dir

更多命令行下载选项，可参见官方文档

SDK 下载

SDK 下载 
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('black-forest-labs/FLUX.2-small-decoder')

Git 下载

请确保 lfs 已经被正确安装

Git 下载 
git lfs install
git clone https://huggingface.co/black-forest-labs/FLUX.2-small-decoder

如果您希望跳过 lfs 大文件下载，可以使用如下命令

跳过 LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/black-forest-labs/FLUX.2-small-decoder

模型文件托管在 Hugging Face Hub，使用 HF CLI / SDK / Git 直接下载，不经过本站。

PyTorch / Transformers 使用

安装 Transformers

安装 Transformers 
pip install -U transformers torch

模型加载和推理

模型加载和推理 
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('black-forest-labs/FLUX.2-small-decoder')
tokenizer = AutoTokenizer.from_pretrained('black-forest-labs/FLUX.2-small-decoder')

模型下载

我们推荐使用命令行或者 ModelScope SDK 来进行模型的下载。

操作指引：在下载前，请先通过如下命令安装 ModelScope：

操作指引 
pip install modelscope

命令行下载

下载完整模型库

下载完整模型库 
modelscope download --model black-forest-labs/FLUX.2-small-decoder

下载单个文件到指定本地文件夹（以下载 README.md 到当前路径下 dir 目录为例）

下载单个文件到指定本地文件夹（以下载 README.md 到当前路径下 dir 目录为例） 
modelscope download --model black-forest-labs/FLUX.2-small-decoder README.md --local_dir ./dir

更多更丰富的命令行下载选项，可参见具体文档

SDK 下载

SDK 下载 
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('black-forest-labs/FLUX.2-small-decoder')

Git 下载

请确保 lfs 已经被正确安装

Git 下载 
git lfs install
git clone https://www.modelscope.cn/black-forest-labs/FLUX.2-small-decoder.git

如果您希望跳过 lfs 大文件下载，可以使用如下命令

跳过 LFS 
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/black-forest-labs/FLUX.2-small-decoder.git

ModelScope 模型页直接下载模型文件；无需将模型文件放在本站服务器。

Notebook 快速开发

下载并安装 ModelScope library

下载并安装 ModelScope library 
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html

模型加载和推理

模型加载和推理 
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

p = pipeline('text-generation', 'black-forest-labs/FLUX.2-small-decoder')

完整文档

来源: HuggingFace

---
license: apache-2.0
language:

  • en

pipeline_tag: image-to-image
tags:
  • text-to-image

  • image-editing

  • flux

  • diffusion-single-file

---

!Comparison Panel

FLUX.2 Small Decoder is a distilled VAE decoder that serves as a drop-in replacement for the standard FLUX.2 decoder. It delivers faster decoding and lower VRAM usage with minimal to zero quality loss. The encoder remains unchanged.

Key Features

1. ~1.4x faster decoding compared to the full decoder.
2. ~1.4x less VRAM at decode time, enabling higher resolutions without running out of memory.
3. ~28M decoder parameters (vs ~50M in the full decoder) thanks to narrower channel widths ([96, 192, 384, 384] vs [128, 256, 512, 512]).
4. Minimal quality loss — images are almost identical.
5. Available under the Apache 2.0 license.

Compatible with all open FLUX.2 models:




Comparison

| Full Decoder | Small Decoder |
|:---:|:---:|
| !Full Decoder | !Small Decoder |

Usage

shell
pip install git+https://github.com/huggingface/diffusers.git
python
import torch
from diffusers import Flux2KleinPipeline, AutoencoderKLFlux2

device = "cuda"
dtype = torch.bfloat16


vae = AutoencoderKLFlux2.from_pretrained("black-forest-labs/FLUX.2-small-decoder", torch_dtype=dtype)
pipe = Flux2KleinPipeline.from_pretrained("black-forest-labs/FLUX.2-klein-4B", vae=vae, torch_dtype=dtype)
pipe.enable_model_cpu_offload()


prompt = "A black cat holding a sign that says 'hello world' in typewriter font"
image = pipe(
    prompt=prompt,
    height=1024,
    width=1024,
    guidance_scale=1.0,
    num_inference_steps=4,
    generator=torch.Generator(device=device).manual_seed(0)
).images[0]
image.save("flux-klein-small-decoder.png")

---

Limitations

  • This model is not intended or able to provide factual information.
  • While the model can output text, text rendered may be inaccurate or subject to distortion.
  • As a statistical model, this checkpoint may represent or amplify biases observed in the training data.
  • The model may fail to generate output that matches the prompts.
  • Prompt following is heavily influenced by the prompting style.

Out-of-Scope Use

This model and its derivatives may not be used outside the scope of the license, including for unlawful, fraudulent, defamatory, abusive, or otherwise violative purposes as further explained in our Usage Policies.

---

Responsible AI Development

Black Forest Labs is committed to responsible model development and deployment. Prior to releasing FLUX.2 [klein] 9B-KV, we evaluated and mitigated a number of risks, including child sexual abuse material (CSAM) and nonconsensual intimate imagery (NCII). For detailed information about our mitigations, evaluation processes, content provenance features, and policies, please see our post: Capable, Open, and Safe: Combating AI
Misuse.

To report safety concerns, contact [email protected].

---

License

This model is licensed under the https://www.apache.org/licenses/LICENSE-2.0.

Trademarks & IP

This project may contain trademarks or logos for projects, products, or services. Use of Black Forest Labs and FLUX trademarks or logos in modified versions of this project must not cause confusion or imply sponsorship or endorsement. Any use of third-party trademarks, intellectual property or logos are subject to those third-party's policies.

查看官方来源