Instructions to use Jorgitosch/yyoorrcchh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jorgitosch/yyoorrcchh with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Jorgitosch/yyoorrcchh", 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 Jorgitosch/yyoorrcchh: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/Jorgitosch/yyoorrcchh/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Jorgitosch/yyoorrcchh/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jorgitosch/yyoorrcchh/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 16147b9c1881d4b5987fec405f7ec62df503dabd8bddce738917093775c48772
- Size of remote file:
- 681 MB
- SHA256:
- 9e1204a492751f7ea64eb8e2a9993083217e59e0d453568380157cd842ded611
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