Instructions to use TaiMingLu/diffusion-architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TaiMingLu/diffusion-architecture 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("TaiMingLu/diffusion-architecture") prompt = "A photo of Johns Hopkins University Modern Building" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
SDXL LoRA DreamBooth - TaiMingLu/lora-trained-xl

- Prompt
- A photo of Johns Hopkins University Modern Building

- Prompt
- A photo of Johns Hopkins University Modern Building

- Prompt
- A photo of Johns Hopkins University Modern Building

- Prompt
- A photo of Johns Hopkins University Modern Building
Model description
These are TaiMingLu/lora-trained-xl LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
The weights were trained using DreamBooth.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
Trigger words
You should use Johns Hopkins University Modern Building to trigger the image generation.
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 TaiMingLu/diffusion-architecture
Base model
stabilityai/stable-diffusion-xl-base-1.0