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
| 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 | |
| <Gallery /> | |
| ## Trigger words | |
| You should use `tcc_mtchbx style` to trigger the image generation. | |
| ## Download model | |
| [Download](/threecrowco/public_loras/tree/main) them in the Files & versions tab. | |