Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
stable-diffusion
stable-diffusion-diffusers
Instructions to use awatterson/dogbooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use awatterson/dogbooth with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("awatterson/dogbooth", dtype=torch.bfloat16, device_map="cuda") prompt = "a photo of [v]dog" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 01d6b7ec60f16a4d9c551e2302a60f233f9be10f55a973c10f2f306f0a893138
- Size of remote file:
- 67 kB
- SHA256:
- eba368ec1766cdf04f328b9e546df98e9e78c756c365cb378e9c926d15959643
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.