Instructions to use neuralvfx/LibreFlux-SAM-ControlNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use neuralvfx/LibreFlux-SAM-ControlNet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("neuralvfx/LibreFlux-SAM-ControlNet", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download examples/libre_flux_control_image.png from neuralvfx/LibreFlux-SAM-ControlNet: direct link, hf CLI and curl.
- Browser
- Download file 149 kB
-
https://huggingface.co/neuralvfx/LibreFlux-SAM-ControlNet/resolve/main/examples/libre_flux_control_image.png
- Command line
-
hf download hf://neuralvfx/LibreFlux-SAM-ControlNet/examples/libre_flux_control_image.png
-
curl -L -o libre_flux_control_image.png https://huggingface.co/neuralvfx/LibreFlux-SAM-ControlNet/resolve/main/examples/libre_flux_control_image.png
149 kB

- Xet hash:
- c6abb5ddbaf5069ba81905f5d9bac54d8980d1f62bca0f8553de63fd62fac507
- Size of remote file:
- 149 kB
- SHA256:
- 8227ba7d8884869f9dc5d3b8950d248038c3dde6181aa45da743ac8651342362
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