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
|
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
| 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 | |
| <Gallery /> | |
| ## Download model | |
| [Download](/falgasdev/zitronstyle/tree/main) them in the Files & versions tab. | |