Instructions to use Guizmus/SDArt_Encapsulated768 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Guizmus/SDArt_Encapsulated768 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_Encapsulated768", 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_Encapsulated768: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/Guizmus/SDArt_Encapsulated768/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Guizmus/SDArt_Encapsulated768/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Guizmus/SDArt_Encapsulated768/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- c04bce01285102e96d3d81d4f4cdc288802f929cf603913e2e33334bdd72042b
- Size of remote file:
- 1.36 GB
- SHA256:
- 41b8a0a2639747d1933694eafae800ac11f93c27aa00a54d1a5cbedae3873358
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