Instructions to use akos2/Matchbox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akos2/Matchbox 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("akos2/Matchbox") prompt = "test" 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: test
output:
url: >-
images/neysalora4_beautiful_photographic_portrait_of_a_woman_with_blonde_hair___wearing_jedi_robes__leather_gloves___detailed__soft_lighting___shot_with_a_medium_format_camera_on_kodak_film_1431324869(1).png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: vintage matchbox artwork
license: apache-2.0
Matchbox
.png)
- Prompt
- test
Model description
test 3
Trigger words
You should use vintage matchbox artwork to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.