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
Update README.md
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README.md
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- output:
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url: images/截圖 2026-01-10 晚上7.39.43.png
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text: Screenshot
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base_model:
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instance_prompt: null
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license: mit
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---
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## Download model
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[Download](/vansonel/A-1/tree/main) them in the Files & versions tab.
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- output:
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url: images/截圖 2026-01-10 晚上7.39.43.png
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text: Screenshot
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base_model:
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- black-forest-labs/FLUX.1-dev
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instance_prompt: null
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license: mit
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---
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## Download model
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[Download](/vansonel/A-1/tree/main) them in the Files & versions tab.
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