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:
- 54f7ee7b7cafcc8f17a760d20654e87edb4840385eff1bfef7215e3944661fd0
- Size of remote file:
- 3.46 GB
- SHA256:
- da97484c0c4c077d8e1831281cd608c0264f7352deca10ece737c36ea9852424
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.