Instructions to use Collos/PedroJr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Collos/PedroJr 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("Collos/PedroJr") 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/WhatsApp Image 2024-12-10 at 09.34.01.jpeg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Pedro
license: mit
Pedro Jr.

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