diff --git a/Dockerfile.tmpl b/Dockerfile.tmpl
index bd78ebf3..b8d14d10 100644
--- a/Dockerfile.tmpl
+++ b/Dockerfile.tmpl
@@ -1,7 +1,7 @@
 {{ if eq .Accelerator "gpu" }}
-FROM us-docker.pkg.dev/colab-images/public/runtime:release-colab-external_20260226-060109_RC00
+FROM us-docker.pkg.dev/colab-images/public/runtime:release-colab-external-images_20260416-060047_RC00
 {{ else }}
-FROM us-docker.pkg.dev/colab-images/public/cpu-runtime:release-colab-external_20260226-060109_RC00
+FROM us-docker.pkg.dev/colab-images/public/cpu-runtime:release-colab-external-images_20260416-060047_RC00
 {{ end}}
 
 ADD kaggle_requirements.txt /kaggle_requirements.txt
@@ -28,6 +28,8 @@ RUN uv pip install --no-build-isolation --no-cache --system "git+https://github.
 # b/468367647: Unpin protobuf, version greater than v5.29.5 causes issues with numerous packages
 RUN uv pip install --system --force-reinstall --no-cache --no-deps torchtune
 RUN uv pip install --system --force-reinstall --no-cache "protobuf==5.29.5"
+# b/493600019: Colab base image ships numba/numba-cuda that do not support NumPy 2.4; upgrade both.
+RUN uv pip install --system --force-reinstall --no-cache numba numba-cuda
 
 # Adding non-package dependencies:
 ADD clean-layer.sh  /tmp/clean-layer.sh
diff --git a/kaggle_requirements.txt b/kaggle_requirements.txt
index 531a6a48..18b5fbdd 100644
--- a/kaggle_requirements.txt
+++ b/kaggle_requirements.txt
@@ -108,8 +108,6 @@ ray
 rgf-python
 s3fs
 scikit-learn
-# Scikit-learn accelerated library for x86
-scikit-learn-intelex>=2023.0.1
 scikit-multilearn
 scikit-optimize
 scikit-plot
diff --git a/tests/test_sklearnex.py b/tests/test_sklearnex.py
deleted file mode 100644
index 5809570a..00000000
--- a/tests/test_sklearnex.py
+++ /dev/null
@@ -1,12 +0,0 @@
-import unittest
-
-import numpy as np
-
-class TestSklearnex(unittest.TestCase):
-    def test_dbscan(self):
-        from sklearnex.cluster import DBSCAN
-        X = np.array([[1., 2.], [2., 2.], [2., 3.],
-            [8., 7.], [8., 8.], [25., 80.]], dtype=np.float32)
-
-        clustering = DBSCAN(eps=3, min_samples=2).fit(X)
-        np.testing.assert_array_equal(np.array([0, 0, 0, 1, 1, -1]), clustering.labels_)
\ No newline at end of file