by frankjoshua
Open source · 5k downloads · 2 likes
FLUX.1 [dev] is an advanced AI model capable of generating images from text descriptions, featuring 12 billion parameters. It stands out for its exceptional output quality, rivaling the best closed models while being more efficient thanks to an innovative training method. Designed to precisely follow instructions, it caters to artists, researchers, and developers seeking to explore new creative or scientific possibilities. Its applications span artistic creation, academic research, and commercial use, provided its non-commercial license is respected. This model distinguishes itself through its open-source approach, fostering innovation while implementing strict ethical safeguards to prevent misuse.
![FLUX.1 [dev] Grid](./dev_grid.jpg)
FLUX.1 [dev] is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions.
For more information, please read our blog post.
FLUX.1 [pro].FLUX.1 [dev] more efficient.FLUX.1 [dev] Non-Commercial License.We provide a reference implementation of FLUX.1 [dev], as well as sampling code, in a dedicated github repository.
Developers and creatives looking to build on top of FLUX.1 [dev] are encouraged to use this as a starting point.
The FLUX.1 models are also available via API from the following sources
FLUX.1 [pro])FLUX.1 [dev] is also available in Comfy UI for local inference with a node-based workflow.
To use FLUX.1 [dev] 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-dev", 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,
height=1024,
width=1024,
guidance_scale=3.5,
num_inference_steps=50,
max_sequence_length=512,
generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("flux-dev.png")
To learn more check out the diffusers documentation
The model and its derivatives may not be used
This model falls under the FLUX.1 [dev] Non-Commercial License.