PaddleClas-en
latest
introduction
installation
quick_start
image_recognition_pipeline
data_preparation
models_training
inference_deployment
models
algorithm_introduction
advanced_tutorials
Image Augmentation
distillation
Knowledge Distillation
Multilabel Classification
Model Quantization and Pruning
Code Overview
How to Contribute to the PaddleClas Community
others
faq_series
PaddleClas-en
advanced_tutorials
distillation
Edit on GitHub
distillation
¶
Knowledge Distillation
Introduction of model compression methods
SSLD
Introduction
Data selection
Experiments
Choice of teacher model
Distillation using large-scale dataset
finetuning using ImageNet1k
Data agmentation and Fix strategy
Some phenomena during the experiment
Application of the distillation model
Instructions
Transfer learning
Object detection
Practice
Configuration
Begin to train the network
Note
Reference