Instructions to use vansonel/Azuma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vansonel/Azuma 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("vansonel/Azuma") prompt = "Screenshot" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/截圖 2026-01-10 晚上7.39.43.png | |
| text: Screenshot | |
| base_model: | |
| - black-forest-labs/FLUX.1-dev | |
| instance_prompt: null | |
| license: mit | |
| # A-1 | |
| <Gallery /> | |
| ## Download model | |
| [Download](/vansonel/A-1/tree/main) them in the Files & versions tab. |