Text-to-Image
Diffusers
lora
diffusers-training
stable-diffusion
stable-diffusion-diffusers
template:sd-lora
stable-diffusion-xl
stable-diffusion-xl-diffusers
Instructions to use kfkas/test_lora_dreambooth_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kfkas/test_lora_dreambooth_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kfkas/test_lora_dreambooth_v2") prompt = "a photo of Korea sks Sungnyemun Gate" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download image_2.png from kfkas/test_lora_dreambooth_v2: direct link, hf CLI and curl.
- Browser
- Download file 992 kB
-
https://huggingface.co/kfkas/test_lora_dreambooth_v2/resolve/main/image_2.png
- Command line
-
hf download hf://kfkas/test_lora_dreambooth_v2/image_2.png
-
curl -L -o image_2.png https://huggingface.co/kfkas/test_lora_dreambooth_v2/resolve/main/image_2.png
992 kB
