Instructions to use Onise/zbase-emma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Onise/zbase-emma 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Onise/zbase-emma") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
emmawatson

- Prompt
- -
Model description
from https://huggingface.co/spaces/malcolmrey/browser
Trigger words
You should use emma watson to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for Onise/zbase-emma
Base model
Tongyi-MAI/Z-Image