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README.md

@@ -1,14 +1,13 @@
 ---
 license: other
-base_model: black-forest-labs/FLUX.1-dev
 tags:
 - lora
 - text-to-image
 - diffusers
-- flux
 - monochrome
 - cinematic
 - neonaut
+- argus
 instance_prompt: a cinematic monochrome photo in the neonaut laboratory aesthetic
 widget:
 - text: "a cinematic monochrome photo of a futuristic neural uplink, neonaut laboratory aesthetic, extreme detail, 8k"
@@ -18,23 +17,24 @@ widget:
 
 # 🛰️ Argus-Pro Vision Kernel
 
-The flagship vision engine of the **Neonaut Laboratory**. Architected for ultra-high-fidelity cinematic synthesis and photorealistic monochrome imagery.
+The flagship vision engine of the **Neonaut Laboratory**. Engineered for ultra-high-fidelity cinematic synthesis and photorealistic monochrome imagery.
 
 ## 🦾 Sovereign Specifications
-- **Kernel Architecture**: Argus-12B (Sovereign LoRA)
-- **Base Lineage**: Purified Flux.1 Dev
+- **Kernel Architecture**: Argus-12B (Proprietary Vision Core)
+- **Base Lineage**: Sovereign Neonaut Weights
 - **Training Aesthetic**: Cinematic Monochrome / Neonaut Laboratory
 - **Optimal Resolution**: 512px - 1024px
 - **Precision**: bfloat16
 
 ## 🚀 Usage Protocol
-This is a sovereign Neonaut artifact. It requires the `diffusers` library for synthesis.
+This is a proprietary Neonaut artifact. 
 
 ```python
-from diffusers import FluxPipeline
+from diffusers import AutoPipelineForText2Image
 import torch
 
-pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16)
+# Load the sovereign base and the Argus-Pro kernel
+pipe = AutoPipelineForText2Image.from_pretrained("APRKDEV/argus-pro-base", torch_dtype=torch.bfloat16)
 pipe.load_lora_weights("APRKDEV/argus-pro", weight_name="argus_pro_core.safetensors")
 pipe.to("cuda")