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![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.FLUX.1 [schnell] can generate high-quality images in only 1 to 4 steps.apache-2.0 licence, the model can be used for personal, scientific, and commercial purposes.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.FLUX.1 [pro])FLUX.1 [schnell] is also available in Comfy UI for local inference with a node-based workflow.FLUX.1 [schnell] with the 🧨 diffusers python library, first install or upgrade diffuserspip install -U diffusersFluxPipeline to run the model1import torch
2from diffusers import FluxPipeline
3
4pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16)
5pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power
6
7prompt = "A cat holding a sign that says hello world"
8image = pipe(
9 prompt,
10 guidance_scale=0.0,
11 num_inference_steps=4,
12 max_sequence_length=256,
13 generator=torch.Generator("cpu").manual_seed(0)
14).images[0]
15image.save("flux-schnell.png")