Instructions to use SpiderSteeped/zilla with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SpiderSteeped/zilla with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SpiderSteeped/zilla") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from SpiderSteeped/zilla: direct link, hf CLI and curl.
- Browser
- Download file 423 Bytes
-
https://huggingface.co/SpiderSteeped/zilla/resolve/main/README.md
- Command line
-
hf download hf://SpiderSteeped/zilla/README.md
-
curl -L -o README.md https://huggingface.co/SpiderSteeped/zilla/resolve/main/README.md
423 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: images/df0r4a3-ffbbd57b-89d6-4dae-9060-9f79d5de1a5e.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
zilla

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