fix doc of quant demo
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@ -42,7 +42,7 @@ python deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global
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# 比如下载提供的训练模型
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wget https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_det_train.tar
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tar -xf ch_ppocr_mobile_v2.0_det_train.tar
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python deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global.pretrain_weights=./ch_ppocr_mobile_v2.0_det_train/best_accuracy Global.save_model_dir=./output/quant_model
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python deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global.pretrain_weights=./ch_ppocr_mobile_v2.0_det_train/best_accuracy Global.save_inference_dir=./output/quant_model
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```
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如果要训练识别模型的量化,修改配置文件和加载的模型参数即可。
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@ -58,7 +58,7 @@ python deploy/slim/quantization/quant.py -c configs/det/det_mv3_db.yml -o Global
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After getting the model after pruning and finetuning we, can export it as inference_model for predictive deployment:
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```bash
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python deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o Global.checkpoints=output/quant_model/best_accuracy Global.save_model_dir=./output/quant_inference_model
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python deploy/slim/quantization/export_model.py -c configs/det/det_mv3_db.yml -o Global.checkpoints=output/quant_model/best_accuracy Global.save_inference_dir=./output/quant_inference_model
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```
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### 5. Deploy
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