Upload app.py with huggingface_hub

app.py

@@ -11,7 +11,7 @@ st.set_page_config(page_title="Dynamic Entropy Genuineness Framework", layout="w
 
 st.title("Dynamic Entropy Genuineness Framework (Version 2.2 Advanced)")
 st.markdown("""
-This application analyzes model trajectories using the **Genuineness Phase Space**. 
+This application analyzes model trajectories using the **Genuineness Phase Space**.
 - **Token Cost (X)**: External information density (surprisal).
 - **Dynamic Genuineness (Y / G-score)**: Internal complexity (entropy variance).
 """)
@@ -39,7 +39,7 @@ if st.button("Analyze Genuineness Trajectory"):
     with st.spinner("Analyzing model dynamics..."):
         # 1. Version 2.2 Model Analysis (d_model=256, n_heads=8, n_layers=6 as trained)
         v2_model = GenuineTransformer(d_model=256, n_heads=8, n_layers=6, vocab_size=1000)
-        
+
         # Load weights
         weights_path = "advanced_genuine_model_v2_2.pt"
         if os.path.exists(weights_path):
@@ -61,13 +61,13 @@ if st.button("Analyze Genuineness Trajectory"):
         with torch.no_grad():
             v2_tokens = text_to_tokens(prompt)
             logits, entropies = v2_model(v2_tokens, g_budget=g_budget)
-            
+
             # G-trajectory: var(entropy) per step across heads
             # entropies: list of [batch, seq, heads]
             g_scores = [float(torch.var(e, dim=-1).mean().detach()) for e in entropies]
-            
+
         col1, col2 = st.columns(2)
-        
+
         with col1:
             st.subheader("Version 2.2: Adaptive G-Trajectory")
             if g_scores:
@@ -81,7 +81,7 @@ if st.button("Analyze Genuineness Trajectory"):
                 ax_v2.set_ylim(0, max(1.0, max(g_scores) * 1.2))
                 ax_v2.legend()
                 st.pyplot(fig_v2)
-                
+
                 st.write(f"**Final G-score**: {round(g_scores[-1], 4)}")
                 st.write(f"**Total Reasoning Steps**: {len(entropies)}")
             else:
@@ -93,12 +93,12 @@ if st.button("Analyze Genuineness Trajectory"):
                     st.subheader("Version 1.0: GPT-2 Phase Space (Interpretability)")
                     v1_model = HookedTransformer.from_pretrained("gpt2-small")
                     results_v1 = run_transformerlens_phase_analysis(v1_model, prompt)
-                    
+
                     mapper = PhaseSpaceMapper()
                     fig_v1, ax_v1 = plt.subplots(figsize=(10, 8))
                     cost = np.array(results_v1["raw_scores"]["cost"])
                     dynamic = np.array(results_v1["raw_scores"]["dynamic"])
-                    
+
                     ax_v1.scatter(cost, dynamic, alpha=0.5, edgecolors='k')
                     ax_v1.set_xlabel("Token Cost (Surprisal)")
                     ax_v1.set_ylabel("Genuineness (Entropy Variance)")
@@ -112,7 +112,7 @@ if st.button("Analyze Genuineness Trajectory"):
                     ax_v1.grid(True, alpha=0.2)
                     ax_v1.legend()
                     st.pyplot(fig_v1)
-                    
+
                     st.write("**Quadrant Distribution**:")
                     st.json(results_v1["phase_space_distribution"])
             except Exception as e: