⚡ Complete Attention Mechanism Tutorial
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⚡ Complete Attention Mechanism
Interactive step-by-step walkthrough of how Q, K, V matrices work together in transformer attention
🔧 Interactive Configuration
Example Text:
The cat sat on (4 tokens)
Hello world how are you (5 tokens)
AI models process text efficiently (5 tokens)
Transformers use attention mechanisms (4 tokens)
Head Dimension:
4 (simplified)
8
16
64 (realistic)
Show Step:
All Steps
1. Q, K, V Creation
2. Q × K^T (Attention Scores)
3. Softmax (Probabilities)
4. Attention × V (Final Output)
⚡ Run Complete Attention Process
🎯 Understanding Each Step
The Complete Attention Formula
Attention(Q, K, V) = softmax(Q × K^T / √d_k) × V
Step 1: Q × K^T → Raw attention scores
Step 2: / √d_k → Scale for stability
Step 3: softmax() → Convert to probabilities
Step 4: × V → Apply to actual content
📚 Explain Each Step in Detail
🔍 Interactive Matrix Explorer
🎯 Key Question:
How does each matrix contribute to the final output?
🔬 Explore Matrix Interactions