Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
dreambooth
Instructions to use askulkarni2/dogbooth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use askulkarni2/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("askulkarni2/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:
- 507cc9290e3d5d36c0687f7fe94ff070fbf760c00ac389bbfd9c7d11b52d8117
- Size of remote file:
- 1.36 GB
- SHA256:
- 011e594b95e5c3fa2d317d6e8958102cd3f0283dccc10ecf0b705ce57cd6ecb0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.