Instructions to use Jemmo/peroduabezza with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jemmo/peroduabezza 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("Jemmo/peroduabezza") prompt = "A teenage Malay woman wearing a traditional headscarf and modest outfit stands confidently at the center of a bustling car showroom scene, surrounded by sleek vehicles and modern architectural details like glass walls and minimalist decor. The subject's facial expression is serene, with fine features visible through detailed skin texture that captures pores and subtle freckles on her cheeks. Her dark hair peeks out from beneath the hijab, adding to her youthful charm." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Welcome to the community
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