Instructions to use shahtab/IvoryStranger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use shahtab/IvoryStranger 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("shahtab/IvoryStranger") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: >-
images/aae4eda29f32c0979aedac94de3bdc5dc37375a9d676bf5d54c5a6ee671d0d2f.webp
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
license: apache-2.0
Ivory Stranger - Flux LoRA

- Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.