Instructions to use Jonjew/NeveCampbell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/NeveCampbell 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/NeveCampbell") prompt = "<lora:Neve_Campbell_Flux:1> The image is a photograph featuring a young woman standing in a cafe, looking at the viewer. smile. The image features a woman with short, dark brown hair styled in a side-swept, slightly tousled manner. She has a fair complexion and is wearing a black, sleeveless dress adorned with sequins that sparkle under the lighting. The dress has a slightly off-the-shoulder neckline and is made of a smooth, reflective material that catches the light, creating a shimmering effect." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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