Instructions to use Wusul/leprechaun-in-pot-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wusul/leprechaun-in-pot-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wusul/leprechaun-in-pot-diffusion", 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 Wusul/leprechaun-in-pot-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/Wusul/leprechaun-in-pot-diffusion/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Wusul/leprechaun-in-pot-diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Wusul/leprechaun-in-pot-diffusion/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- bb135a6c40cf4ba1b75d2b2f48454a2b3ddb547a2a190e3aee4ccce957b6da92
- Size of remote file:
- 681 MB
- SHA256:
- bf84a7cc98089355972d155ca71f5de3f901cd91b5e543b896613ea7ca3d5a49
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