Instructions to use Ffgsd/iora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ffgsd/iora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zai-org/GLM-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Ffgsd/iora") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/2061b783246b4d85817a905822a67666.jpeg
text: '-'
base_model: zai-org/GLM-Image
instance_prompt: null
license: openrail
lora

- Prompt
- -
Model description
lora
Download model
Download them in the Files & versions tab.