Instructions to use sunday96/stepania2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sunday96/stepania2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SG161222/Realistic_Vision_V1.4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("sunday96/stepania2") prompt = "stepania" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA DreamBooth - stepania2
These are LoRA adaption weights for SG161222/Realistic_Vision_V1.4. The weights were trained on the instance prompt "stepania" using DreamBooth. You can find some example images in the following.
- Downloads last month
- 3
Model tree for sunday96/stepania2
Base model
SG161222/Realistic_Vision_V1.4