Instructions to use sd-dreambooth-library/abaya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sd-dreambooth-library/abaya with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sd-dreambooth-library/abaya", 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 text_encoder/pytorch_model.bin from sd-dreambooth-library/abaya: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/sd-dreambooth-library/abaya/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://sd-dreambooth-library/abaya/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sd-dreambooth-library/abaya/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 4baf86588da699c3f027d919f530437da3ee82a4f8a5e17c6b9782f50a383636
- Size of remote file:
- 246 MB
- SHA256:
- 9bd8dcce2705c3def7d0c35cefea4630bfcdf065b6b8a68e001d3994b90ab493
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.