Instructions to use fofr/flux-black-light with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fofr/flux-black-light with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fofr/flux-black-light") prompt = "a BLKLGHT portrait photo" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add generated example
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README.md
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- text: a BLKLGHT portrait photo
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output:
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url: images/example_sd110h4sf.png
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---
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- text: a BLKLGHT portrait photo
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output:
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url: images/example_sd110h4sf.png
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- text: a portrait photo with BLKLGHT makeup in a club
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output:
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url: images/example_am912xsus.png
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images/example_am912xsus.png
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