Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use HumpyDonkey/monse_all_dress_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use HumpyDonkey/monse_all_dress_v1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("HumpyDonkey/monse_all_dress_v1", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of a monse dress" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DreamBooth - HumpyDonkey/monse_all_dress_v1
This is a dreambooth model derived from runwayml/stable-diffusion-v1-5. The weights were trained on a photo of a monse dress using DreamBooth. You can find some example images in the following.
DreamBooth for the text encoder was enabled: False.
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Model tree for HumpyDonkey/monse_all_dress_v1
Base model
runwayml/stable-diffusion-v1-5