Instructions to use threecrowco/public_loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use threecrowco/public_loras with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("leejet/FLUX.2-klein-9B-GGUF", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("threecrowco/public_loras") prompt = "Make the image tcc_mtchbx style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: >-
images/_app_ai-toolkit_output_tcc_mtchbx_v0.1_samples_1780000822933__000000700_1.jpg
text: Make the image tcc_mtchbx style
base_model: leejet/FLUX.2-klein-9B-GGUF
instance_prompt: tcc_mtchbx style
license: apache-2.0
Matchbox F2K

- Prompt
- Make the image tcc_mtchbx style
Trigger words
You should use tcc_mtchbx style to trigger the image generation.
Download model
Download them in the Files & versions tab.