README.md

---
language:
- en
license: apache-2.0
tags:
- text-to-image
- image-generation
- flux
widget:
- text: >-
    cctv camera shot of guys shooting guns at a scary werewolf running towards
    them at a WAWA gas station. The werewolf is running right towards the people
    and the muzzle flash can be seen from the tip of there guns. People and cars
    are in the background
  output:
    url: images/example_jgi3tnjg3.png

---

![FLUX.1 [schnell] Grid](./schnell_grid.jpeg)

`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](https://blackforestlabs.ai/announcing-black-forest-labs/).

# 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](https://github.com/black-forest-labs/flux).
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
- [bfl.ml](https://docs.bfl.ml/) (currently `FLUX.1 [pro]`)
- [replicate.com](https://replicate.com/collections/flux)
- [fal.ai](https://fal.ai/models/fal-ai/flux/schnell)
- [mystic.ai](https://www.mystic.ai/black-forest-labs/flux1-schnell)

## ComfyUI
`FLUX.1 [schnell]` is also available in [Comfy UI](https://github.com/comfyanonymous/ComfyUI) for local inference with a node-based workflow.

## Diffusers
To use `FLUX.1 [schnell]` with the 🧨 diffusers python library, first install or upgrade diffusers

```shell
pip install -U diffusers
```

Then you can use `FluxPipeline` to run the model

```python
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,
    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](https://huggingface.co/docs/diffusers/main/en/api/pipelines/flux) documentation

---
# 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.