diff --git a/deepmd/infer/deep_pot.py b/deepmd/infer/deep_pot.py
index 1e7ed52c39..3c5fb28f6e 100644
--- a/deepmd/infer/deep_pot.py
+++ b/deepmd/infer/deep_pot.py
@@ -26,6 +26,18 @@ class DeepPot(DeepEval):
     default_tf_graph : bool
         If uses the default tf graph, otherwise build a new tf graph for evaluation
 
+    Examples
+    --------
+    >>> from deepmd.infer import DeepPot
+    >>> import numpy as np
+    >>> dp = DeepPot('graph.pb')
+    >>> coord = np.array([[1,0,0], [0,0,1.5], [1,0,3]]).reshape([1, -1])
+    >>> cell = np.diag(10 * np.ones(3)).reshape([1, -1])
+    >>> atype = [1,0,1]
+    >>> e, f, v = dp.eval(coord, cell, atype)
+    
+    where `e`, `f` and `v` are predicted energy, force and virial of the system, respectively.
+
     Warnings
     --------
     For developers: `DeepTensor` initializer must be called at the end after
diff --git a/deepmd/infer/model_devi.py b/deepmd/infer/model_devi.py
index 2f8ea83335..74f33322a6 100644
--- a/deepmd/infer/model_devi.py
+++ b/deepmd/infer/model_devi.py
@@ -110,6 +110,17 @@ def calc_model_devi(coord,
     model_devi : numpy.ndarray, `n_frames x 7`
         Model deviation results. The first column is index of steps, the other 6 columns are
         max_devi_v, min_devi_v, avg_devi_v, max_devi_f, min_devi_f, avg_devi_f.
+    
+    Examples
+    --------
+    >>> from deepmd.infer import calc_model_devi
+    >>> from deepmd.infer import DeepPot as DP
+    >>> import numpy as np
+    >>> coord = np.array([[1,0,0], [0,0,1.5], [1,0,3]]).reshape([1, -1])
+    >>> cell = np.diag(10 * np.ones(3)).reshape([1, -1])
+    >>> atype = [1,0,1]
+    >>> graphs = [DP("graph.000.pb"), DP("graph.001.pb")]
+    >>> model_devi = calc_model_devi(coord, cell, atype, graphs)
     '''
     if nopbc:
         box = None