Instructions to use wkplhc/ue3.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wkplhc/ue3.0 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("wkplhc/ue3.0") prompt = "anime style, female, long black hair, piercing violet eyes, A mysterious woman dressed as a witch, wearing a dark, elegant, long-sleeved sheer dress adorned with intricate golden details, large black witches' hat, long flowing hair, intense and focused expression, dark cloudy atmospheric background, dramatic lighting that highlights her face and costume, centered composition with a medium close-up framing, the mood is mystical and powerful. . aidmaMJ6.1, aidmafluxpro1.1" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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- Prompt
- anime style, female, long black hair, piercing violet eyes, A mysterious woman dressed as a witch, wearing a dark, elegant, long-sleeved sheer dress adorned with intricate golden details, large black witches' hat, long flowing hair, intense and focused expression, dark cloudy atmospheric background, dramatic lighting that highlights her face and costume, centered composition with a medium close-up framing, the mood is mystical and powerful. . aidmaMJ6.1, aidmafluxpro1.1
Trigger words
You should use ue5 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 wkplhc/ue3.0
Base model
black-forest-labs/FLUX.1-dev