Instructions to use Barathrum17/mateo23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Barathrum17/mateo23 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("Barathrum17/mateo23") prompt = "acac" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/001 — копия.png
text: acac
parameters:
negative_prompt: acac
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: m4t3o
license: mit
aca

- Prompt
- acac
- Negative Prompt
- acac
Trigger words
You should use m4t3o to trigger the image generation.
Download model
Download them in the Files & versions tab.