diff --git a/LICENSE b/LICENSE
index f6126d011a9a..b23afba158af 100644
--- a/LICENSE
+++ b/LICENSE
@@ -1,6 +1,6 @@
                                  Apache License
                            Version 2.0, January 2004
-                        http://www.apache.org/licenses/
+                        https://www.apache.org/licenses/
 
    TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
 
@@ -192,7 +192,7 @@
    you may not use this file except in compliance with the License.
    You may obtain a copy of the License at
 
-       http://www.apache.org/licenses/LICENSE-2.0
+       https://www.apache.org/licenses/LICENSE-2.0
 
    Unless required by applicable law or agreed to in writing, software
    distributed under the License is distributed on an "AS IS" BASIS,
diff --git a/README.md b/README.md
index fb9e9bc4a0d1..58878cfd0409 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,22 @@
-<!--- Licensed to the Apache Software Foundation (ASF) under one -->
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one
+ or more contributor license agreements.  See the NOTICE file
+ distributed with this work for additional information
+ regarding copyright ownership.  The ASF licenses this file
+ to you under the Apache License, Version 2.0 (the
+ "License"); you may not use this file except in compliance
+ with the License.  You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing,
+ software distributed under the License is distributed on an
+ "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ KIND, either express or implied.  See the License for the
+ specific language governing permissions and limitations
+ under the License.
+-->
+
 <!--- or more contributor license agreements.  See the NOTICE file -->
 <!--- distributed with this work for additional information -->
 <!--- regarding copyright ownership.  The ASF licenses this file -->
@@ -6,7 +24,7 @@
 <!--- "License"); you may not use this file except in compliance -->
 <!--- with the License.  You may obtain a copy of the License at -->
 
-<!---   http://www.apache.org/licenses/LICENSE-2.0 -->
+<!---   https://www.apache.org/licenses/LICENSE-2.0 -->
 
 <!--- Unless required by applicable law or agreed to in writing, -->
 <!--- software distributed under the License is distributed on an -->
diff --git a/docs/how_to/tutorials/customize_opt.py b/docs/how_to/tutorials/customize_opt.py
index 2e2747d61fc5..ed1571cd3b51 100644
--- a/docs/how_to/tutorials/customize_opt.py
+++ b/docs/how_to/tutorials/customize_opt.py
@@ -55,6 +55,31 @@
 from tvm import IRModule, relax
 from tvm.relax.frontend import nn
 
+# Note: This tutorial requires TVM CUDA support.
+# If you encounter import errors:
+# 1. First try: pip install tvm-ffi (from 3rdparty/tvm-ffi)
+# 2. If that fails: Build TVM from source with CUDA enabled
+# Build instructions: https://tvm.apache.org/docs/install/from_source.html
+
+try:
+    import tvm.relax.backend.cuda.cublas as _cublas
+except ImportError as e:
+    import sys
+
+    print("Error: TVM CUDA support required for this tutorial.", file=sys.stderr)
+    print("Solutions:", file=sys.stderr)
+    print("  1. Install tvm-ffi: pip install tvm-ffi", file=sys.stderr)
+    print(
+        "  2. Build TVM with CUDA: https://tvm.apache.org/docs/install/from_source.html",
+        file=sys.stderr,
+    )
+    sys.exit(1)
+# If import succeeds, continue with tutorial
+# If you encounter 'No module named ''tvm_ffi''' error,
+# you need to build TVM from source with CUDA enabled.
+# Build instructions: https://tvm.apache.org/docs/install/from_source.html
+
+
 ######################################################################
 # Composable IRModule Optimization
 # --------------------------------
@@ -222,4 +247,3 @@ def transform_module(self, mod: IRModule, _ctx: tvm.transform.PassContext) -> IR
 # We can easily compose the optimization passes and customize the optimization for different parts
 # of the computation graph. The flexibility of the optimization pipeline enables us to quickly
 # iterate the optimization and improve the performance of the model.
-#