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
https://huggingface.co/VERUMNNODE/OS
#2
by VERUMNNODE - opened
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VERUMNNODE OS β Sovereign Text-to-Image Intelligence
High-performance, sovereign-grade text-to-image generation system built on advanced Diffusion + LoRA architecture. Designed for speed, fidelity, modularity, and artistic control across public, institutional, and experimental domains.
π Deployment Interfaces
| Interface | URL |
|---|---|
| π₯οΈ Web Interface | Launch Web UI |
| π Inference API | API Access |
| π§ Model Repository | Repository & Weights |
βοΈ Features & Capabilities
- π¨ Prompt-to-image generation with LoRA efficiency
- β‘ Optimized inference: 2β5s (GPU)
- π οΈ LoRA fine-tuning support
- π Scalable resolutions up to 1024x1024
- π« Mitigates common failure patterns (e.g. blur, low detail)
- π§© Suitable for multi-domain applications: art, research, civic media
π Quick Start β Python
from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"VERUMNNODE/OS",
torch_dtype=torch.float16,
use_safetensors=True
)
pipe = pipe.to("cuda") if torch.cuda.is_available() else pipe
# Simple generation
image = pipe("Futuristic observatory in the desert, cinematic style").images[0]
image.save("observatory.png")
VERUMNNODE changed pull request status to open
VERUMNNODE changed pull request status to merged