Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion
stable-diffusion-diffusers
lora
template:sd-lora
Instructions to use vaishali18/my-dreambooth-project2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vaishali18/my-dreambooth-project2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("vaishali18/my-dreambooth-project2") prompt = "photo of a ghg construction site worker wearing helmet without vest" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
AutoTrain LoRA DreamBooth - vaishali18/my-dreambooth-project2
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on photo of a ghg construction site worker wearing helmet without vest using DreamBooth. LoRA for the text encoder was enabled: False.
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Model tree for vaishali18/my-dreambooth-project2
Base model
runwayml/stable-diffusion-v1-5