diff --git a/example/auto_compression/detection/configs/picodet_reader.yml b/example/auto_compression/detection/configs/picodet_reader.yml
new file mode 100644
index 0000000000000000000000000000000000000000..389673367517322d0bec107886d4ed799083965a
--- /dev/null
+++ b/example/auto_compression/detection/configs/picodet_reader.yml
@@ -0,0 +1,31 @@
+metric: COCO
+num_classes: 80
+
+# Datset configuration
+TrainDataset:
+  !COCODataSet
+    image_dir: train2017
+    anno_path: annotations/instances_train2017.json
+    dataset_dir: dataset/coco/
+
+EvalDataset:
+  !COCODataSet
+    image_dir: val2017
+    anno_path: annotations/instances_val2017.json
+    dataset_dir: dataset/coco/
+
+eval_height: &eval_height 416
+eval_width: &eval_width 416
+eval_size: &eval_size [*eval_height, *eval_width]
+
+worker_num: 0
+
+EvalReader:
+  inputs_def:
+    image_shape: [1, 3, *eval_height, *eval_width]
+  sample_transforms:
+  - Decode: {}
+  - Resize: {interp: 2, target_size: *eval_size, keep_ratio: False}
+  - NormalizeImage: {is_scale: true, mean: [0.485,0.456,0.406], std: [0.229, 0.224,0.225]}
+  - Permute: {}
+  batch_size: 32
diff --git a/example/auto_compression/detection/configs/picodet_s_qat_dis.yaml b/example/auto_compression/detection/configs/picodet_s_qat_dis.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..563a6653f9d4a3f30f927425e071672a7e6669e1
--- /dev/null
+++ b/example/auto_compression/detection/configs/picodet_s_qat_dis.yaml
@@ -0,0 +1,43 @@
+Global:
+  reader_config: ./configs/picodet_reader.yml
+  input_list: ['image', 'scale_factor']
+  Evaluation: True
+  model_dir: ./picodet_s_416_coco_lcnet/
+  model_filename: model.pdmodel
+  params_filename: model.pdiparams
+
+Distillation:
+  alpha: 1.0
+  loss: l2
+  node:
+  - conv2d_138.tmp_1
+  - tmp_2
+  - conv2d_146.tmp_1
+  - tmp_5
+  - conv2d_162.tmp_1
+  - tmp_11
+  - conv2d_154.tmp_1
+  - tmp_8
+
+Quantization:
+  use_pact: true
+  activation_quantize_type: 'moving_average_abs_max'
+  weight_bits: 8
+  activation_bits: 8
+  quantize_op_types:
+  - conv2d
+  - depthwise_conv2d
+
+TrainConfig:
+  train_iter: 8000
+  eval_iter: 1000
+  learning_rate:  
+    type: CosineAnnealingDecay
+    learning_rate: 0.00001
+    T_max: 8000
+  optimizer_builder:
+    optimizer:
+      type: SGD
+    weight_decay: 4.0e-05
+
+