Instructions to use smit-mehta/orange-juice-ad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use smit-mehta/orange-juice-ad 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("smit-mehta/orange-juice-ad") prompt = "photos of the orange juice bottle used for orange juice brand advertisement." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
LoRA DreamBooth - smit-mehta/orange-juice-ad
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on photos of the orange juice bottle used for orange juice brand advertisement. using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Special VAE used for training: None.
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Model tree for smit-mehta/orange-juice-ad
Base model
stabilityai/stable-diffusion-xl-base-1.0