Update app.py

app.py

@@ -12,15 +12,15 @@ import matplotlib.pyplot as plt
 import pandas as pd
 from sklearn.manifold import TSNE
 
-# Load pretrained transformer model
+
 tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/all-MiniLM-L6-v2")
 base_model = AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L6-v2")
 
-# Set device
+
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 base_model.to(device)
 
-# Define a projection network for meta-learning adaptation
+
 class ProjectionHead(nn.Module):
     def __init__(self, input_dim=384, hidden_dim=128, output_dim=384):
         super().__init__()
@@ -64,7 +64,7 @@ class ConceptHierarchy:
 
 concept_hierarchy = ConceptHierarchy()
 
-# Advanced Memory System with Uncertainty and Drift Detection
+
 class CognitiveMemory:
     def __init__(self, max_length=100):
         self.samples = deque(maxlen=max_length)
@@ -353,7 +353,7 @@ def train_sample(text, label):
 
 # Gradio UI
 with gr.Blocks() as app:
-    gr.Markdown("# Advanced Cognitive Labeling System")
+    gr.Markdown("# Vers3Dynamics Labeling System")
     gr.Markdown("### This system features meta-learning, active learning, uncertainty quantification, and concept drift detection")
     
     with gr.Row():