diff --git a/deepmd_utils/utils/argcheck.py b/deepmd_utils/utils/argcheck.py
index 390742edcc..29886dd54f 100644
--- a/deepmd_utils/utils/argcheck.py
+++ b/deepmd_utils/utils/argcheck.py
@@ -365,7 +365,7 @@ def descrpt_se_atten_common_args():
     doc_seed = "Random seed for parameter initialization"
     doc_exclude_types = "The excluded pairs of types which have no interaction with each other. For example, `[[0, 1]]` means no interaction between type 0 and type 1."
     doc_attn = "The length of hidden vectors in attention layers"
-    doc_attn_layer = "The number of attention layers. Note that model compression of `se_atten` is only enabled when attn_layer==0 and stripped_type_embedding is True"
+    doc_attn_layer = "The number of attention layers."
     doc_attn_dotr = "Whether to do dot product with the normalized relative coordinates"
     doc_attn_mask = "Whether to do mask on the diagonal in the attention matrix"
 
diff --git a/doc/freeze/compress.md b/doc/freeze/compress.md
index 54b9baf7ca..87d4699d2b 100644
--- a/doc/freeze/compress.md
+++ b/doc/freeze/compress.md
@@ -148,6 +148,8 @@ The model compression interface requires the version of DeePMD-kit used in the o
 
 Descriptors with `se_e2_a`, `se_e3`, `se_e2_r` and `se_atten_v2` types are supported by the model compression feature. `Hybrid` mixed with the above descriptors is also supported.
 
+Notice: Model compression for the `se_atten_v2` descriptor is exclusively designed for models with the training parameter {ref}`attn_layer <model/descriptor[se_atten_v2]/attn_layer>` set to 0.
+
 **Available activation functions for descriptor:**
 
 - tanh
diff --git a/doc/model/train-se-atten.md b/doc/model/train-se-atten.md
index 79c7149a61..0ed73fe203 100644
--- a/doc/model/train-se-atten.md
+++ b/doc/model/train-se-atten.md
@@ -120,6 +120,8 @@ We highly recommend using the version 2.0 of the attention-based descriptor `"se
 
 Practical evidence demonstrates that `"se_atten_v2"` offers better and more stable performance compared to `"se_atten"`.
 
+Notice: Model compression for the `se_atten_v2` descriptor is exclusively designed for models with the training parameter {ref}`attn_layer <model/descriptor[se_atten_v2]/attn_layer>` set to 0.
+
 ### Fitting `"ener"`
 
 DPA-1 only supports `"ener"` fitting type, and you can refer [here](train-energy.md) for detailed information.