language:
- en
license: apache-2.0
tags:
- text-to-image
- image-generation
- flux
base_model:
- Qwen/QwQ-32B-Preview
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
- Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives.
- Trained using latent adversarial diffusion distillation,
FLUX.1 [schnell]
can generate high-quality images in only 1 to 4 steps. - 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
- bfl.ml (currently
FLUX.1 [pro]
) - replicate.com
- fal.ai
- mystic.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 -U diffusers
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,
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
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.