Update QuickStart.md (microsoft#2884)

docs/en_US/Compressor/QuickStart.md

@@ -123,7 +123,7 @@ It means following the algorithm's default setting for compressed operations wit
 
 #### Quantization specific keys
 
-**If you use quantization algorithms, you need to specify more keys. If you use pruning algorithms, you can safely skip these keys**
+Besides the keys explained above, if you use quantization algorithms you need to specify more keys in `config_list`, which are explained below.
 
 * __quant_types__ : list of string. 
 
@@ -148,6 +148,31 @@ when the value is int type, all quantization types share same bits length. eg.
 }
 ```
 
+The following example shows a more complete `config_list`, it uses `op_names` (or `op_types`) to specify the target layers along with the quantization bits for those layers.
+```
+configure_list = [{
+        'quant_types': ['weight'],        
+        'quant_bits': 8, 
+        'op_names': ['conv1']
+    }, {
+        'quant_types': ['weight'],
+        'quant_bits': 4,
+        'quant_start_step': 0,
+        'op_names': ['conv2']
+    }, {
+        'quant_types': ['weight'],
+        'quant_bits': 3,
+        'op_names': ['fc1']
+        },
+       {
+        'quant_types': ['weight'],
+        'quant_bits': 2,
+        'op_names': ['fc2']
+        }
+]
+```
+In this example, 'op_names' is the name of layer and four layers will be quantized to different quant_bits.
+
 ### APIs for Updating Fine Tuning Status
 
 Some compression algorithms use epochs to control the progress of compression (e.g. [AGP](https://nni.readthedocs.io/en/latest/Compressor/Pruner.html#agp-pruner)), and some algorithms need to do something after every minibatch. Therefore, we provide another two APIs for users to invoke: `pruner.update_epoch(epoch)` and `pruner.step()`.
@@ -168,4 +193,4 @@ pruner.export_model(model_path='model.pth')
 pruner.export_model(model_path='model.pth', mask_path='mask.pth', onnx_path='model.onnx', input_shape=[1, 1, 28, 28])
 ```
 
-If you want to really speed up the compressed model, please refer to [NNI model speedup](./ModelSpeedup.md) for details.
+If you want to really speed up the compressed model, please refer to [NNI model speedup](./ModelSpeedup.md) for details.