diff --git a/MindChemistry/applications/crystalflow/test_crystalflow.py b/MindChemistry/applications/crystalflow/test_crystalflow.py
index ffce4881fb9075c96dc7b1eb0afdd56a5a0a8779..18e0a919913db4ffdaa32bf8e77f5b8936385dbc 100644
--- a/MindChemistry/applications/crystalflow/test_crystalflow.py
+++ b/MindChemistry/applications/crystalflow/test_crystalflow.py
@@ -7,6 +7,7 @@ import mindspore.numpy as mnp
 from mindspore import nn, ops, Tensor, mint, load_checkpoint, load_param_into_net
 from mindchemistry.graph.loss import L2LossMask
 import numpy as np
+import urllib.request
 
 
 from models.cspnet import CSPNet
@@ -33,6 +34,13 @@ class SinusoidalTimeEmbeddings(nn.Cell):
             (ops.Sin()(embeddings), ops.Cos()(embeddings)))
         return embeddings
 
+def download_file(url, filename):
+    try:
+        urllib.request.urlretrieve(url, filename)
+        print(f"File downloaded successfully: {filename}")
+    except Exception as e:
+        print(f"Failed to download file: {e}")
+
 def test_cspnet():
     """test cspnet.py"""
     ms.set_seed(1234)
@@ -153,7 +161,8 @@ def test_loss():
 
     cspnet = CSPNet(num_layers=6, hidden_dim=512, num_freqs=256)
     cspflow = CSPFlow(cspnet)
-    mindspore_ckpt = load_checkpoint("./torch2ms_ckpt/ms_flow.ckpt")
+    download_file('https://download-mindspore.osinfra.cn/mindscience/mindchemistry/crystalflow/ms_flow.ckpt', 'ms_flow.ckpt')
+    mindspore_ckpt = load_checkpoint("ms_flow.ckpt")
     load_param_into_net(cspflow, mindspore_ckpt)
 
     loss_func_mse = L2LossMask(reduction='mean')