Instructions to use ktkeller/lily-phoebe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ktkeller/lily-phoebe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ktkeller/lily-phoebe", dtype=torch.bfloat16, device_map="cuda") prompt = "This is Lilysk" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download text_encoder/pytorch_model.bin from ktkeller/lily-phoebe: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/ktkeller/lily-phoebe/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://ktkeller/lily-phoebe/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ktkeller/lily-phoebe/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 35b1e401632e7d937655c2817128c90d34a6945dfad3551e0931a30fe4b7d776
- Size of remote file:
- 492 MB
- SHA256:
- aeb936d3b3f337cc48f5a809b35e7406c3e472f0833dba13d0bc150930fa9e6b
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