Instructions to use Jonjew/ElleFanning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/ElleFanning 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("Jonjew/ElleFanning") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Elle Fanning (FLUX + SDXL)

- Prompt
- -
Model description
FROM https://civitai.com/models/265004/elle-fanning-flux-sdxl?modelVersionId=884626
Strength 1 0.8-1.2. No keywords needed!
About this version
FLUX v1.0 :
Trained on FLUX dev with 70 photos of Elle Fanning with detailed captions. Tested on FLUX 1.D (full) and FLUX fp8 and FLUX nf4 ! Use around strength 0.8-1.2. No keywords needed! Distilled CFG around 1-4 and CFG 1.0 (without negative prompt). Clipskip 1. Can be used for example as follows:
Positive : {Artstyle, Character and scene description in usual FLUX fashion}, <lora:ellefanning_local_flux_1_standard-000040:1>
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for Jonjew/ElleFanning
Base model
black-forest-labs/FLUX.1-dev