Text-to-Image
Diffusers
TensorBoard
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use bsuutari/path_to_saved_model_rafa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bsuutari/path_to_saved_model_rafa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bsuutari/path_to_saved_model_rafa", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of rafa suutari" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
DreamBooth - bsuutari/path_to_saved_model_rafa
This is a dreambooth model derived from CompVis/stable-diffusion-v1-4. The weights were trained on a photo of rafa suutari 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 bsuutari/path_to_saved_model_rafa
Base model
CompVis/stable-diffusion-v1-4