Instructions to use Matb09/alexander-smith with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Matb09/alexander-smith 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("Matb09/alexander-smith") prompt = "a pair of alexander smith shoes" 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: a pair of alexander smith shoes
output:
url: images/photo_of_a_pair_of_alexander_smith_shoes_5.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: alexander, smith
license: apache-2.0
alexander-smith

- Prompt
- a pair of alexander smith shoes
Trigger words
You should use alexander to trigger the image generation.
You should use smith to trigger the image generation.
Download model
Weights for this model are available in Safetensors,PyTorch format.
Download them in the Files & versions tab.