Instructions to use ukwildcat/sister_sarah-dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ukwildcat/sister_sarah-dataset with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ideogram-ai/ideogram-4-fp8", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ukwildcat/sister_sarah-dataset") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Sister_sarah

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Model description
Ultra-realistic lifestyle photo of Eva Saint sitting on the edge of a neatly made bed in a satin cream robe, one knee pulled close, holding a coffee mug and looking toward the camera with a playful smile. Soft morning window light, luxury apartment bedroom, realistic shadows, natural skin texture, intimate but tasteful, iPhone photo quality, vertical 9:16.

Trigger words
You should use sister_sarah to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for ukwildcat/sister_sarah-dataset
Base model
ideogram-ai/ideogram-4-fp8











