Instructions to use vcollos/VitorCollos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vcollos/VitorCollos 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("vcollos/VitorCollos") prompt = "Portrait of Vitor Collos in a office" 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: Portrait of Vitor Collos in a office
output:
url: images/IMG_0047.WEBP
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Vitor
license: mit
Vitor Collos
- Prompt
- Portrait of Vitor Collos in a office
Model description
Inferences of Vitor
Trigger words
You should use Vitor to trigger the image generation.
Download model
Weights for this model are available in PyTorch,Safetensors format.
Download them in the Files & versions tab.