Instructions to use falgasdev/zitronstyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use falgasdev/zitronstyle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("falgasdev/zitronstyle") prompt = "masterpiece, best quality, anime coloring, anime screencap," image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from falgasdev/zitronstyle: direct link, hf CLI and curl.
- Browser
- Download file 436 Bytes
-
https://huggingface.co/falgasdev/zitronstyle/resolve/main/README.md
- Command line
-
hf download hf://falgasdev/zitronstyle/README.md
-
curl -L -o README.md https://huggingface.co/falgasdev/zitronstyle/resolve/main/README.md
436 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/zitron.png
text: masterpiece, best quality, anime coloring, anime screencap,
parameters:
negative_prompt: blurry ugly bad
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: null
zitronstyle

- Prompt
- masterpiece, best quality, anime coloring, anime screencap,
- Negative Prompt
- blurry ugly bad
Download model
Download them in the Files & versions tab.