Instructions to use APRKDEV/argus-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use APRKDEV/argus-pro with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("APRKDEV/argus-pro") prompt = "a cinematic monochrome photo of a futuristic neural uplink, neonaut laboratory aesthetic, extreme detail, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Upload README.md with huggingface_hub
Browse files
README.md
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---
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license: other
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base_model: black-forest-labs/FLUX.1-dev
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tags:
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- lora
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- text-to-image
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- diffusers
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- flux
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- monochrome
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- cinematic
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- neonaut
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instance_prompt: a cinematic monochrome photo in the neonaut laboratory aesthetic
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widget:
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- text: "a cinematic monochrome photo of a futuristic neural uplink, neonaut laboratory aesthetic, extreme detail, 8k"
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output:
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url: "https://huggingface.co/APRKDEV/argus-pro/resolve/main/argus_pro_core.safetensors"
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---
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# 🛰️ Argus-Pro Vision Kernel
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The flagship vision engine of the **Neonaut Laboratory**. Architected for ultra-high-fidelity cinematic synthesis and photorealistic monochrome imagery.
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## 🦾 Sovereign Specifications
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- **Kernel Architecture**: Argus-12B (Sovereign LoRA)
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- **Base Lineage**: Purified Flux.1 Dev
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- **Training Aesthetic**: Cinematic Monochrome / Neonaut Laboratory
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- **Optimal Resolution**: 512px - 1024px
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- **Precision**: bfloat16
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## 🚀 Usage Protocol
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This is a sovereign Neonaut artifact. It requires the `diffusers` library for synthesis.
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```python
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from diffusers import FluxPipeline
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import torch
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pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
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pipe.load_lora_weights("APRKDEV/argus-pro", weight_name="argus_pro_core.safetensors")
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pipe.to("cuda")
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prompt = "a cinematic monochrome photo in the neonaut laboratory aesthetic, [YOUR PROMPT HERE]"
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image = pipe(prompt, num_inference_steps=30, guidance_scale=3.5).images[0]
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image.save("neonaut_synthesis.png")
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```
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## ⚖️ License
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Authorized under the **Icarus Open-Source License (IOSL)**. Managed by **APRK**.
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