Instructions to use hiddenbox/pore_dream5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hiddenbox/pore_dream5 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_V5.1_noVAE", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("hiddenbox/pore_dream5") prompt = "a photo of a1sfv dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA DreamBooth - hiddenbox/pore_dream5
These are LoRA adaption weights for SG161222/Realistic_Vision_V5.1_noVAE. The weights were trained on a photo of a1sfv dog using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
- Downloads last month
- 2
Model tree for hiddenbox/pore_dream5
Base model
SG161222/Realistic_Vision_V5.1_noVAE


