Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Docty/dreambooth-restshow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Docty/dreambooth-restshow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Docty/dreambooth-restshow", dtype=torch.bfloat16, device_map="cuda") prompt = "very dark skin orban_restshow ghanaian woman with giant breasts, giant lips, big butt, braids, at park, off shoulder dress, smiling, busty, 21 years old, side view" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DreamBooth - Docty/dreambooth-restshow
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on very dark skin orban_restshow ghanaian woman with giant breasts, giant lips, big butt, braids, at park, off shoulder dress, smiling, busty, 21 years old, side view using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for Docty/dreambooth-restshow
Base model
CompVis/stable-diffusion-v1-4