diff --git a/.kokoro/github/ubuntu/gpu/build.sh b/.kokoro/github/ubuntu/gpu/build.sh
index 2571d0d048..f3b0095977 100644
--- a/.kokoro/github/ubuntu/gpu/build.sh
+++ b/.kokoro/github/ubuntu/gpu/build.sh
@@ -25,7 +25,7 @@ if [ "${KERAS2:-0}" == "1" ]
 then
    echo "Keras2 detected."
    pip install -r requirements-common.txt --progress-bar off
-   pip install tensorflow-text==2.14 tensorflow==2.14 keras-core
+   pip install tensorflow-text==2.15 tensorflow[and-cuda]~=2.15 keras-core
 
 elif [ "$KERAS_BACKEND" == "tensorflow" ]
 then
diff --git a/.kokoro/github/ubuntu/gpu/keras2/presubmit.cfg b/.kokoro/github/ubuntu/gpu/keras2/presubmit.cfg
index e988e3b375..7e971ac96d 100644
--- a/.kokoro/github/ubuntu/gpu/keras2/presubmit.cfg
+++ b/.kokoro/github/ubuntu/gpu/keras2/presubmit.cfg
@@ -7,5 +7,10 @@ action {
   }
 }
 
+env_vars: {
+   key: "KERAS2"
+   value: "1"
+}
+
 # Set timeout to 60 mins from default 180 mins
 timeout_mins: 60
\ No newline at end of file
diff --git a/keras_nlp/models/whisper/whisper_tokenizer.py b/keras_nlp/models/whisper/whisper_tokenizer.py
index b1406b0a04..cd4da7d15f 100644
--- a/keras_nlp/models/whisper/whisper_tokenizer.py
+++ b/keras_nlp/models/whisper/whisper_tokenizer.py
@@ -23,7 +23,7 @@
 
 def _load_dict(dict_or_path):
     if isinstance(dict_or_path, str):
-        with open(dict_or_path, "r") as f:
+        with open(dict_or_path, "r", encoding="utf-8") as f:
             dict_or_path = json.load(f)
     return dict_or_path
 
diff --git a/keras_nlp/tokenizers/byte_pair_tokenizer.py b/keras_nlp/tokenizers/byte_pair_tokenizer.py
index 133c9565b0..b799874d2a 100644
--- a/keras_nlp/tokenizers/byte_pair_tokenizer.py
+++ b/keras_nlp/tokenizers/byte_pair_tokenizer.py
@@ -292,7 +292,7 @@ def __init__(
         super().__init__(dtype=dtype, **kwargs)
 
         if isinstance(vocabulary, str):
-            with open(vocabulary, "r") as f:
+            with open(vocabulary, "r", encoding="utf-8") as f:
                 self.vocabulary = json.load(f)
         elif isinstance(vocabulary, dict):
             self.vocabulary = vocabulary.copy()