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:
- d7636a77ecc102f7cd7ce52569dc25f2823659452ec5575d49827e171124a272
- Size of remote file:
- 1.74 GB
- SHA256:
- 4ea1d423a6a1bbbc62abff5f5a83341f9618fc17cab5f3827f9a2a0a492cc1c5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.