Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion
stable-diffusion-diffusers
lora
template:sd-lora
Instructions to use skshoheb33/my-dreambooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use skshoheb33/my-dreambooth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("skshoheb33/my-dreambooth") prompt = "photo of a xyz" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
AutoTrain LoRA DreamBooth - skshoheb33/my-dreambooth
These are LoRA adaption weights for stabilityai/stable-diffusion-2-1. The weights were trained on photo of a xyz using DreamBooth. LoRA for the text encoder was enabled: False.
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Model tree for skshoheb33/my-dreambooth
Base model
stabilityai/stable-diffusion-2-1