Instructions to use wolfer45/zimage-emmastone-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wolfer45/zimage-emmastone-v2 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("wolfer45/zimage-emmastone-v2") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
|
Download README.md from wolfer45/zimage-emmastone-v2: direct link, hf CLI and curl.
- Browser
- Download file 487 Bytes
-
https://huggingface.co/wolfer45/zimage-emmastone-v2/resolve/main/README.md
- Command line
-
hf download hf://wolfer45/zimage-emmastone-v2/README.md
-
curl -L -o README.md https://huggingface.co/wolfer45/zimage-emmastone-v2/resolve/main/README.md
487 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/31.jpg
text: '-'
base_model: Tongyi-MAI/Z-Image-Turbo
instance_prompt: zimage-emmastone-v2
zimage-emmastone-v2

- Prompt
- -
Model description
zimage-emmastone-v2
Trigger words
You should use zimage-emmastone-v2 to trigger the image generation.
Download model
Download them in the Files & versions tab.