Instructions to use mindlywork/Pixel_Art_FLUX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mindlywork/Pixel_Art_FLUX 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mindlywork/Pixel_Art_FLUX") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
- template:sd-lora
widget:
- text: '-'
output:
url: images/4e5b595c-adaa-4df8-9b3c-48ae57cac52f.webp
base_model: black-forest-labs/FLUX.1-schnell
instance_prompt: Pixel_Art_FLUX
license: cc
Pixel_Art_FLUX

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