Instructions to use koankoan/lilcyborg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use koankoan/lilcyborg with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("koankoan/lilcyborg", dtype=torch.bfloat16, device_map="cuda") prompt = "lilcyborg" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from koankoan/lilcyborg: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/koankoan/lilcyborg/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://koankoan/lilcyborg/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/koankoan/lilcyborg/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 49e897d142602415aa3c2c10bfe7200fdd42806723d390c465fef9cff6487cc5
- Size of remote file:
- 492 MB
- SHA256:
- ab63413f7f1d8f20f81a3934585cb8ba5e14a358e6606dd0d21aab76e233c8a7
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