FLUX.1 [schnell] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post.

Key Features

1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives.

2. Trained using latent adversarial diffusion distillation, FLUX.1 [schnell] can generate high-quality images in only 1 to 4 steps.

3. Released under the apache-2.0 licence, the model can be used for personal, scientific, and commercial purposes.

Usage

We provide a reference implementation of FLUX.1 [schnell], as well as sampling code, in a dedicated github repository. Developers and creatives looking to build on top of FLUX.1 [schnell] are encouraged to use this as a starting point.

API Endpoints

The FLUX.1 models are also available via API from the following sources

1. bfl.ml (currently FLUX.1 [pro])

2. replicate.com

3. fal.ai

ComfyUI

FLUX.1 [schnell] is also available in Comfy UI for local inference with a node-based workflow.

Diffusers

To use FLUX.1 [schnell] with the ? diffusers python library, first install or upgrade diffusers

pip install git+https://github.com/huggingface/diffusers.git

Then you can use FluxPipeline to run the model

import torch

from diffusers import FluxPipeline



pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)

pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power



prompt = "A cat holding a sign that says hello world"

image = pipe(

    prompt,

    guidance_scale=0.0,

    output_type="pil",

    num_inference_steps=4,

    max_sequence_length=256,

    generator=torch.Generator("cpu").manual_seed(0)

).images[0]

image.save("flux-schnell.png")

To learn more check out the diffusers documentation

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Limitations

• This model is not intended or able to provide factual information.

• As a statistical model this checkpoint might amplify existing societal biases.

• The model may fail to generate output that matches the prompts.

• Prompt following is heavily influenced by the prompting-style.

Out-of-Scope Use

The model and its derivatives may not be used

• In any way that violates any applicable national, federal, state, local or international law or regulation.

• For the purpose of exploiting, harming or attempting to exploit or harm minors in any way; including but not limited to the solicitation, creation, acquisition, or dissemination of child exploitative content.

• To generate or disseminate verifiably false information and/or content with the purpose of harming others.

• To generate or disseminate personal identifiable information that can be used to harm an individual.

• To harass, abuse, threaten, stalk, or bully individuals or groups of individuals.

• To create non-consensual nudity or illegal pornographic content.

• For fully automated decision making that adversely impacts an individual's legal rights or otherwise creates or modifies a binding, enforceable obligation.

• Generating or facilitating large-scale disinformation campaigns.

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