Deploy clean Steve Jobs Sovereign Guild edition of Experimentlab profile

README.md

@@ -35,19 +35,28 @@ We bridge deep academic theory with extreme computational efficiency:
 
 ## 🏛️ Flagship Model Architectures
 
-
+```mermaid
+graph LR
+    A["Raw STEM Corpora (Ai2 Dolma, SymPy CAS, arXiv)"] --> B["Vigyan Sovereign Pretraining"]
+    B --> C["Vigyan MoE (1.5B - 3B 4x Experts)"]
+    B --> D["BitNet 1.58-Bit Ternary QAT"]
+    B --> E["Doctoral STEM Series (7B - 32B)"]
+    C --> F["Edge CPU & NPU (GGUF / bitnet.cpp)"]
+    D --> F
+    E --> G["Vigyan Pro Workstation"]
+```
 
 ### 1. 🌟 Sparse Mixture of Experts (MoE)
-* **[](https://huggingface.co/Experimentlab/Vigyan-1.5B-4x-MoE)**: Ultra-fast 4-expert routed SLM delivering 7B-class STEM reasoning at a fraction of inference memory.
-* **[](https://huggingface.co/Experimentlab/Vigyan-3B-4x-MoE)**: Advanced multi-expert router tuned on symbolic logic and scientific problem-solving.
+* **[`Vigyan-1.5B-4x-MoE`](https://huggingface.co/Experimentlab/Vigyan-1.5B-4x-MoE)**: Ultra-fast 4-expert routed SLM delivering 7B-class STEM reasoning at a fraction of inference memory.
+* **[`Vigyan-3B-4x-MoE`](https://huggingface.co/Experimentlab/Vigyan-3B-4x-MoE)**: Advanced multi-expert router tuned on symbolic logic and scientific problem-solving.
 
 ### 2. ⚡ 1.58-Bit Ternary BitNet Architectures
-* **[](https://huggingface.co/Experimentlab/vigyan-3b-1.58bit-qat)**: Pure 1.58-bit weights {-1, 0, +1} trained via Quantization-Aware Training (QAT). Eliminates power-hungry matrix multiplication in favor of integer addition, enabling offline execution on low-power ARM and x86 chips.
+* **[`vigyan-3b-1.58bit-qat`](https://huggingface.co/Experimentlab/vigyan-3b-1.58bit-qat)**: Pure 1.58-bit weights {-1, 0, +1} trained via Quantization-Aware Training (QAT). Eliminates power-hungry matrix multiplication in favor of integer addition, enabling offline execution on low-power ARM and x86 chips.
 
 ### 3. 🔬 Doctoral & Silicon Hardware Series
-* **[](https://huggingface.co/Experimentlab/olmo2-7b-silicon-rtl-eda)**: Hardware silicon EDA specialist for Verilog RTL synthesis, timing constraints, and digital logic verification.
-* **[](https://huggingface.co/Experimentlab/olmo2-7b-phd-pure-math)**: Specialization in pure mathematics, formal proofs, topology, and abstract algebra.
-* **[](https://huggingface.co/Experimentlab/olmo2-7b-biomed-chem)**: Deep biochemistry, computational medicine, and molecular modeling.
+* **[`olmo2-7b-silicon-rtl-eda`](https://huggingface.co/Experimentlab/olmo2-7b-silicon-rtl-eda)**: Hardware silicon EDA specialist for Verilog RTL synthesis, timing constraints, and digital logic verification.
+* **[`olmo2-7b-phd-pure-math`](https://huggingface.co/Experimentlab/olmo2-7b-phd-pure-math)**: Specialization in pure mathematics, formal proofs, topology, and abstract algebra.
+* **[`olmo2-7b-biomed-chem`](https://huggingface.co/Experimentlab/olmo2-7b-biomed-chem)**: Deep biochemistry, computational medicine, and molecular modeling.
 
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