Instructions to use Jonjew/JoanSeverance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/JoanSeverance 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/JoanSeverance") prompt = "photo of j04ns3v3r4nc3, a woman wearing an elegant dress, standing in the red carpet of a film festival, <lora:ty-j04ns3v3r4nc3:1>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Joan Severance

- Prompt
- photo of j04ns3v3r4nc3, a woman wearing an elegant dress, standing in the red carpet of a film festival, <lora:ty-j04ns3v3r4nc3:1>
Model description
FROM https://civitai.com/models/1293697/joan-severance-90s-flux-lora?modelVersionId=1460024
Trigger j04ns3v3r4nc3
Strength 1
Trigger words
You should use j04ns3v3r4nc3 to trigger the image generation.
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/JoanSeverance
Base model
black-forest-labs/FLUX.1-dev