Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use wittenberg/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wittenberg/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wittenberg/model", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of cartoon girl face" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth - wittenberg/model
This is a dreambooth model derived from CompVis/stable-diffusion-v1-1. The weights were trained on a photo of cartoon girl face using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
- Downloads last month
- 3
Model tree for wittenberg/model
Base model
CompVis/stable-diffusion-v1-1