Instructions to use Khruna/saja with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Khruna/saja 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("Khruna/saja") prompt = "a (portrait, upper body focus) photograph of (1girl, 24 years old, slight smile)>,<lora:ZH_DishaPSD1.5_v1_r1:0.9>, zh_dishap, solo, realistic, brown eyes, dark skin, looking at viewer, make-up, wearing (dress)," image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
saja

- Prompt
- a (portrait, upper body focus) photograph of (1girl, 24 years old, slight smile)>,<lora:ZH_DishaPSD1.5_v1_r1:0.9>, zh_dishap, solo, realistic, brown eyes, dark skin, looking at viewer, make-up, wearing (dress),
- Negative Prompt
- bad-hands-5, low resolution, (monochrome:1.2), (grayscale:1.2), signature, watermark, (worst quality:2), (low quality:2), (normal quality:2), ((cropped, out of frame)), ((jewelry)), ((earrings)), 0001SoftRealisticNegativeV10, ((cleavage))
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 Khruna/saja
Base model
black-forest-labs/FLUX.1-dev