Instructions to use Kvikontent/Parcifique with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kvikontent/Parcifique with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Kvikontent/Parcifique") prompt = "A beautiful photo of a realistic eye" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 94fb4d0bcda59b2537b230ad69a5bb1955c11fa7abffd5a80192e25dc21d6c16
- Size of remote file:
- 19 MB
- SHA256:
- 154ce1f5637aebee7db8f94d257122494187ebae25b13092fe62b4821226c33c
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