Instructions to use CutePickle/FLUX.1-Fill-dev-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CutePickle/FLUX.1-Fill-dev-nf4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CutePickle/FLUX.1-Fill-dev-nf4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Flux.1Fill-dev-nf4
This is a custom Flux.1 Fill pipeline that combines:
- Base pipeline:
black-forest-labs/FLUX.1-dev - Transformer:
sayakpaul/FLUX.1-Fill-dev-nf4 - Text Encoder 2:
sayakpaul/FLUX.1-Fill-dev-nf4
Usage
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"CutePickle/FLUX.1-Fill-dev-nf4",
torch_dtype=torch.bfloat16
)
pipe.enable_model_cpu_offload()
image = pipe(
prompt="A cyberpunk cityscape at night",
image=init_image,
mask_image=mask
).images[0]
image.save("output.png")
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Model tree for CutePickle/FLUX.1-Fill-dev-nf4
Base model
black-forest-labs/FLUX.1-dev