Instructions to use Burroughs352/Gabbi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Burroughs352/Gabbi 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("Burroughs352/Gabbi") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Burroughs352/Gabbi: direct link, hf CLI and curl.
- Browser
- Download file 433 Bytes
-
https://huggingface.co/Burroughs352/Gabbi/resolve/main/README.md
- Command line
-
hf download hf://Burroughs352/Gabbi/README.md
-
curl -L -o README.md https://huggingface.co/Burroughs352/Gabbi/resolve/main/README.md
433 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/z-image_00847_.png
text: '-'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: Gabbi
Gabbi

- Prompt
- -
Model description
Gabbi
Trigger words
You should use Gabbi to trigger the image generation.
Download model
Download them in the Files & versions tab.