Text-to-Image
Diffusers
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use mfsuve/dreambooth-lamp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mfsuve/dreambooth-lamp with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mfsuve/dreambooth-lamp", dtype=torch.bfloat16, device_map="cuda") prompt = "a cc lamp" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
DreamBooth - mfsuve/dreambooth-lamp
This is a DreamBooth model by Mustafa Furkan Süve derived from runwayml/stable-diffusion-v1-5 and finetuned on the images of the lamp below.

The weights and the text encoder were trained on the prompt "a cc lamp" using DreamBooth.
You can find some example images below generated with the following prompts:
| Prompt | sketch drawing of a cc lamp, black and white, hand drawn, pencil art |
|---|---|
| Negative Prompt | duplicate realistic |
| Prompt | cc lamp emitting purple light |
|---|---|
| Negative Prompt | duplicate |
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Base model
runwayml/stable-diffusion-v1-5










