Instructions to use Gurusha/dreembooth_two_hands_touching with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Gurusha/dreembooth_two_hands_touching with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Gurusha/dreembooth_two_hands_touching") prompt = "closeup of two human sks hands holding each other" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
LoRA DreamBooth - Gurusha/dreembooth_two_hands_touching
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on closeup of two human sks hands holding each other using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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Model tree for Gurusha/dreembooth_two_hands_touching
Base model
stabilityai/stable-diffusion-xl-base-1.0