Update README.md

README.md

@@ -37,19 +37,19 @@ The SNP model was benchmarked against five leading semantic models (OpenAI, Cohe
 All were tested across three analytical dimensions: **reasoning divergence**, **semantic variance**, and **emotional coherence.**
 
 ### 🧩 Embedding Cosine Similarity Matrix
-![Embedding Similarity Matrix](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/resolve/main/embedding_matrix.png)
+![Embedding Similarity Matrix](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/blob/main/embedding_matrix.png)
 
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 ### 🧭 PCA Projection — Reasoning Geometry
-![PCA Projection](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/resolve/main/pca_projection.png)
+![PCA Projection](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/blob/main/pca_projection.png)
 
 SNP shows **distinct geometric separation**, indicating that its embedding space encodes **reasoning-based dimensions** rather than surface-level semantic proximity.
 
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 ### 🧮 Centroid Distance & Variance
-![Centroid Distance](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/resolve/main/centroid_variance.png)
+![Centroid Distance](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/blob/main/centroid_variance.png)
 
 | Metric | Meaning | SNP Result | Industry Avg |
 |--------|----------|-------------|---------------|
@@ -60,21 +60,21 @@ SNP shows **distinct geometric separation**, indicating that its embedding space
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 ### 🧭 Reasoning Spectrum — Divergence vs Coherence
-![Reasoning Spectrum](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/resolve/main/reasoning_spectrum.png)
+![Reasoning Spectrum](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/blob/main/reasoning_spectrum.png)
 
 SNP exhibits a **10× higher RDI score**, representing far more structured divergence and emotional reasoning coherence.
 
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 ### 🧬 Cognitive Geometry Radar
-![Cognitive Geometry Radar](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/resolve/main/cognitive_radar.png)
+![Cognitive Geometry Radar](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/blob/main/cognitive_radar.png)
 
 SNP demonstrates a balance of **low variance (tight semantics)** and **high reasoning divergence**, indicating a unique dual encoding capability.
 
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 ### 💓 Cognitive–Emotional Geometry Radar
-![Cognitive Emotional Geometry Radar](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/resolve/main/emotional_radar.png)
+![Cognitive Emotional Geometry Radar](https://huggingface.co/366dEgrees/SNP-Universal-Embedding/blob/main/emotional_radar.png)
 
 This final radar integrates *Reasoning Divergence (RDI)*, *Semantic Tightness (1/σ²)*, and *Emotional Coherence (ΔAffect)* —  
 showing that SNP uniquely aligns *rational and emotional embeddings*.