Instructions to use Optimusdev/bd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Optimusdev/bd 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("Optimusdev/bd") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: images/d39a8778752ba3c8640321270fc65170.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: birdog
license: mit
birdog

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