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
- Draw Things
- DiffusionBee
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.
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Model tree for threecrowco/public_loras
Base model
black-forest-labs/FLUX.2-klein-9B Quantized
leejet/FLUX.2-klein-9B-GGUF