Model Optimization
AI Model Performance Enhancement for Production
Advanced techniques for model compression, acceleration, and performance optimization
faster after optimization
model size reduction
energy savings
Model Optimization Techniques
Q Quantization
Numerical Precision Reduction
Reduce data size from 32-bit to 16-bit, 8-bit or lower
Dynamic Quantization
Adjust precision dynamically based on data
P Model Pruning
Structured Pruning
Unstructured Pruning
Magnitude-based Pruning
Knowledge Distillation
Knowledge Transfer Process
Teacher Model
Large, high-performance model with superior accuracy
Student Model
Smaller model learning from teacher's knowledge
Soft Targets
Use probability distributions instead of hard labels
Optimization Results
Model Size
Inference Speed
Accuracy
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