Instructions to use zac/oliy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zac/oliy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("RunDiffusion/Juggernaut-XL-v9", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("zac/oliy") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from zac/oliy: direct link, hf CLI and curl.
- Browser
- Download file 419 Bytes
-
https://huggingface.co/zac/oliy/resolve/main/README.md
- Command line
-
hf download hf://zac/oliy/README.md
-
curl -L -o README.md https://huggingface.co/zac/oliy/resolve/main/README.md
419 Bytes
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/image - 2024-04-24T101346.181.png
base_model: RunDiffusion/Juggernaut-XL-v9
instance_prompt: null
license: apache-2.0
oly

- Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.