Instructions to use fchghfgh/ginga4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fchghfgh/ginga4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("pmczip/FLUX.2-klein-9B_Models", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fchghfgh/ginga4") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/what-is-real-estate.webp
text: '-'
- output:
url: images/IMG_1243.JPG.jpeg
text: '-'
base_model: pmczip/FLUX.2-klein-9B_Models
instance_prompt: null
license: apache-2.0
gingalala

- Prompt
- -

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