Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Yulaaa/dogbooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yulaaa/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("Yulaaa/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:
- fe0f12660fef7aadc2f44f0b46e610b22784f1a47cecb21796fa082e8e001322
- Size of remote file:
- 1.74 GB
- SHA256:
- 220e7ed6345d84c402b40ddd303cb2dc10988f356473262ae2732364db2ea461
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.