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🗜️ Topic 33: Model Distillation & Compression

Course: NLP Advanced | Section 4: Pre-trained Language Models Topic: Knowledge Distillation,…

Overview

🗜️ Topic 33: Model Distillation & Compression — Quick Facts

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Topic 1

📌 Overview: Models Ko Chhota Kyun Banana Hai?

📚 ` The Size Problem: ┌──────────────────────────────────────────────────┐ │ Model │ Params…

Topic 2

🔷 1. Knowledge Distillation

💡 ` Knowledge Distillation: Teacher → Student…

Topic 3

🟢 2. Quantization

🎯 ` Quantization: Reduce Number Precision FP32 → INT8: 4× compression, ~2× faster…

Topic 4

🟡 3. Pruning

⭐ ` Pruning: Remove Unnecessary Parameters Like trimming a tree — cut unimportant branches!…

Topic 5

🟣 4. Weight Sharing (ALBERT-style)

🔑 ` Weight Sharing: Reuse Parameters Across Layers BERT-Base: 12 layers × unique weights =…

Topic 6

📊 Compression Methods Comparison

✨ ` ┌──────────────┬──────────┬──────────┬──────────┬──────────┐ │ │ Distill │ Quantize │…

Topic 7

💻 Complete Python Implementation

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First 2-3 layers: capture basic…

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Middle layers: most redundant →…

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Last 1-2 layers: task-specific →…

Topic 8

❓ Quiz — Model Compression Mastery

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A) Model faster ho jaata hai

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B) Softmax output softer ho jaata…

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C) Model size reduce hoti hai

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D) Training loss badhta hai

Topic 9

🧭 Navigation

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Quick Quiz

Quiz — Question 1

🗜️ Topic 33: Model Distillation & Compression ka sabse sahi definition kya hai?

Complete! 🎉

🗜️ Topic 33: Model Distillation & Compression Complete!

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