Instructions to use thatboymentor/lorafan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thatboymentor/lorafan 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("thatboymentor/lorafan") prompt = "34124" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/db46ef7f9a13607340df0fcc8626b1dd.jpg
text: '34124'
parameters:
negative_prompt: '4343532'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: null
license: bigscience-openrail-m
lorafan

- Prompt
- 34124
- Negative Prompt
- 4343532
Download model
Download them in the Files & versions tab.