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
File size: 353 Bytes
df54af2 1c6ab7d df54af2 1c6ab7d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ---
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. |