Instructions to use Guizmus/SDArt_Encapsulated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Guizmus/SDArt_Encapsulated with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Guizmus/SDArt_Encapsulated", 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 Guizmus/SDArt_Encapsulated: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/Guizmus/SDArt_Encapsulated/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Guizmus/SDArt_Encapsulated/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Guizmus/SDArt_Encapsulated/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 1490cca12a891ce6f1ff9b9e98ca6f8556ac8a187af697f134fb1c18ed33650f
- Size of remote file:
- 492 MB
- SHA256:
- e66a3fb645a0867b2d6c6c78c7207e661923ce4793ae2dcc11ea7d82c7c16393
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