Instructions to use NitroZJ/SQ1_Flux_Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NitroZJ/SQ1_Flux_Lora 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("NitroZJ/SQ1_Flux_Lora") prompt = "SQ1" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
SQ1

- Prompt
- SQ1
Trigger words
You should use SQ1 to trigger the image generation.
Download model
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Model tree for NitroZJ/SQ1_Flux_Lora
Base model
black-forest-labs/FLUX.1-dev