Instructions to use juliocho/sticker_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use juliocho/sticker_lora 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("juliocho/sticker_lora") prompt = "Fire" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Sticker-like

- Prompt
- Fire
Model description
A LoRA trained with 50 images of sticker-like images with the image name beneath it with a variety of fonts.
Download model
Download them in the Files & versions tab.
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Model tree for juliocho/sticker_lora
Base model
Tongyi-MAI/Z-Image-Turbo