Instructions to use williamberman/dreambooth_if_dog with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use williamberman/dreambooth_if_dog with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("williamberman/dreambooth_if_dog", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download watermarker/diffusion_pytorch_model.bin from williamberman/dreambooth_if_dog: direct link, hf CLI and curl.
- Browser
- Download file 62.5 kB
-
https://huggingface.co/williamberman/dreambooth_if_dog/resolve/main/watermarker/diffusion_pytorch_model.bin
- Command line
-
hf download hf://williamberman/dreambooth_if_dog/watermarker/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/williamberman/dreambooth_if_dog/resolve/main/watermarker/diffusion_pytorch_model.bin
62.5 kB
- Xet hash:
- b32e620077ea34bf4d23963be2aa7de565419136c32080d3f93fbbaead4e64db
- Size of remote file:
- 62.5 kB
- SHA256:
- febe0a7711807b6700cc91b38bbcaa129568a1915cff9b9ccfa25e5b700ad639
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.