Instructions to use JoeProAI/Jobious with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JoeProAI/Jobious with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("JoeProAI/Jobious") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/img-mPfiKsKDQd8hpZvVd8i8lb.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Jobious
license: mit
Jobious

- Prompt
- -
Model description
Test Jobious
Trigger words
You should use Jobious to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.