Instructions to use VERUMNNODE/OS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use VERUMNNODE/OS with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("google/magenta-realtime,THUDM/GLM-4.1V-9B-Thinking,moonshotai/Kimi-K2-Instruct,tencent/Hunyuan-A13B-Instruct,nanonets/Nanonets-OCR-s", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("VERUMNNODE/OS") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Update README.md
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README.md
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@@ -28,3 +28,21 @@ https://replit.com/@raugustoxavier1/DecentralizedWorkstation
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[Download](/VERUMNNODE/OS/tree/main) them in the Files & versions tab.
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[Download](/VERUMNNODE/OS/tree/main) them in the Files & versions tab.
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---
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tags:
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- text-to-image
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- lora
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- diffusers
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- template:diffusion-lora
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widget:
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- output:
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url: images/@rafaela6015-wisetag.png
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text: 'Logo'
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- output:
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url: images/QRCode_FΓ‘cil.jpg
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text: 'QR Code'
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base_model: black-forest-labs/FLUX.1-schnell
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instance_prompt: null
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license: mit
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---
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