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
File size: 549 Bytes
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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.
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