Instructions to use liming518/RodVerFlux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use liming518/RodVerFlux 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("liming518/RodVerFlux") prompt = "Image I created with this lora at 0.1, to get more face variety" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Upload 2 files
Browse files- README.md +31 -0
- RodVerFlux.safetensors +3 -0
README.md
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---
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tags:
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- text-to-image
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- lora
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- diffusers
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- template:diffusion-lora
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widget:
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- text: cropped original img from lora creator
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output:
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url: images/Img0.jpg
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- text: clothed latina prompt
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output:
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url: images/img1.png
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- text: bikini latina prompt
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output:
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url: images/img2.png
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- text: clothed asian prompt
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output:
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url: images/img3.png
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: null
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---
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Civitai lora for Flux1dev
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Original image for this lora and images i made:
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<Gallery />
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RodVerFlux.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5e4b7a20b77e8cd52f5441d056a16f07744955a1fe950d8e7fb15b429a251897
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size 171969440
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