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
- Draw Things
- DiffusionBee
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README.md
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# LibreFLUX-ControlNet Inference (WIP)
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This model is a
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- Attention Masking
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- Running inference with CFG.
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## Status
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Work in progress.
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### Compatibility
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# LibreFLUX-ControlNet Inference (WIP)
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This model is a ControlNet Inference Pipeline, trained on top of LibreFLUX using [https://github.com/NeuralVFX/LibreFLUX-ControlNet]
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It incorperates:
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- Attention Masking
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- Running inference with CFG.
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## Status
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Work in progress. Code is being transferred and adapted from my larger project.
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### Compatibility
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