diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 7ce42889..2d57149a 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -8,7 +8,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        os: [ubuntu-20.04]
+        os: [ubuntu-24.04]
     steps:
       - name: Check out repository
         uses: actions/checkout@v2
@@ -56,7 +56,7 @@ jobs:
     needs: python-setup
     strategy:
       matrix:
-        os: [ubuntu-20.04]
+        os: [ubuntu-24.04]
         pytest_target: [models, layers]
     name: test-${{ matrix.pytest_target }}
     steps:
diff --git a/onnx2kerastl/operation_layers.py b/onnx2kerastl/operation_layers.py
index 0aea8ddf..dd4455f8 100644
--- a/onnx2kerastl/operation_layers.py
+++ b/onnx2kerastl/operation_layers.py
@@ -231,14 +231,19 @@ def convert_reduce_min(node, params, layers, lambda_func, node_name, keras_name)
         axes = params.get("axes")
     elif len(node.input) == 2:
         axes = layers.get(node.input[1])
+    else:
+        axes = None
     noop_with_empty_axes = bool(params.get("noop_with_empty_axes", False))
     keepdims = params.get("keepdims", True)
     if noop_with_empty_axes and params.get("axes") is None:
         layers[node_name] = layers[node.input[0]]
     else:
-        layers[node_name] = tf_math_reduce_min(layers[node.input[0]], axis=axes, keepdims=keepdims,
+        if axes is None:
+            layers[node_name] = tf_math_reduce_min(layers[node.input[0]], keepdims=keepdims,
+                                               tf_name=f"{params['cleaned_name']}_min")
+        else:
+            layers[node_name] = tf_math_reduce_min(layers[node.input[0]], axis=axes, keepdims=keepdims,
                                                tf_name=f"{params['cleaned_name']}_min")
-
 
 def convert_reduce_prod(node, params, layers, lambda_func, node_name, keras_name):
     """
diff --git a/poetry.lock b/poetry.lock
index 7bd46317..3f542c50 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -19,7 +19,7 @@ version = "2.4.4"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "aiohappyeyeballs-2.4.4-py3-none-any.whl", hash = "sha256:a980909d50efcd44795c4afeca523296716d50cd756ddca6af8c65b996e27de8"},
     {file = "aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745"},
@@ -31,7 +31,7 @@ version = "3.10.11"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "aiohttp-3.10.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5077b1a5f40ffa3ba1f40d537d3bec4383988ee51fbba6b74aa8fb1bc466599e"},
     {file = "aiohttp-3.10.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:8d6a14a4d93b5b3c2891fca94fa9d41b2322a68194422bef0dd5ec1e57d7d298"},
@@ -144,7 +144,7 @@ version = "1.3.1"
 description = "aiosignal: a list of registered asynchronous callbacks"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "aiosignal-1.3.1-py3-none-any.whl", hash = "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17"},
     {file = "aiosignal-1.3.1.tar.gz", hash = "sha256:54cd96e15e1649b75d6c87526a6ff0b6c1b0dd3459f43d9ca11d48c339b68cfc"},
@@ -176,7 +176,7 @@ version = "5.0.1"
 description = "Timeout context manager for asyncio programs"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "async_timeout-5.0.1-py3-none-any.whl", hash = "sha256:39e3809566ff85354557ec2398b55e096c8364bacac9405a7a1fa429e77fe76c"},
     {file = "async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3"},
@@ -188,7 +188,7 @@ version = "25.1.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "attrs-25.1.0-py3-none-any.whl", hash = "sha256:c75a69e28a550a7e93789579c22aa26b0f5b83b75dc4e08fe092980051e1090a"},
     {file = "attrs-25.1.0.tar.gz", hash = "sha256:1c97078a80c814273a76b2a298a932eb681c87415c11dee0a6921de7f1b02c3e"},
@@ -284,6 +284,7 @@ files = [
     {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"},
     {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"},
 ]
+markers = {main = "platform_machine == \"x86_64\" or platform_machine == \"arm64\""}
 
 [[package]]
 name = "cffi"
@@ -466,6 +467,7 @@ files = [
     {file = "charset_normalizer-3.4.1-py3-none-any.whl", hash = "sha256:d98b1668f06378c6dbefec3b92299716b931cd4e6061f3c875a71ced1780ab85"},
     {file = "charset_normalizer-3.4.1.tar.gz", hash = "sha256:44251f18cd68a75b56585dd00dae26183e102cd5e0f9f1466e6df5da2ed64ea3"},
 ]
+markers = {main = "platform_machine == \"x86_64\" or platform_machine == \"arm64\""}
 
 [[package]]
 name = "colorama"
@@ -486,7 +488,7 @@ version = "15.0.1"
 description = "Colored terminal output for Python's logging module"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934"},
     {file = "coloredlogs-15.0.1.tar.gz", hash = "sha256:7c991aa71a4577af2f82600d8f8f3a89f936baeaf9b50a9c197da014e5bf16b0"},
@@ -504,7 +506,7 @@ version = "2.14.4"
 description = "HuggingFace community-driven open-source library of datasets"
 optional = false
 python-versions = ">=3.8.0"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "datasets-2.14.4-py3-none-any.whl", hash = "sha256:29336bd316a7d827ccd4da2236596279b20ca2ac78f64c04c9483da7cbc2459b"},
     {file = "datasets-2.14.4.tar.gz", hash = "sha256:ef29c2b5841de488cd343cfc26ab979bff77efa4d2285af51f1ad7db5c46a83b"},
@@ -559,7 +561,7 @@ version = "0.3.7"
 description = "serialize all of Python"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "dill-0.3.7-py3-none-any.whl", hash = "sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e"},
     {file = "dill-0.3.7.tar.gz", hash = "sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03"},
@@ -589,7 +591,7 @@ version = "3.16.1"
 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "filelock-3.16.1-py3-none-any.whl", hash = "sha256:2082e5703d51fbf98ea75855d9d5527e33d8ff23099bec374a134febee6946b0"},
     {file = "filelock-3.16.1.tar.gz", hash = "sha256:c249fbfcd5db47e5e2d6d62198e565475ee65e4831e2561c8e313fa7eb961435"},
@@ -619,7 +621,7 @@ version = "1.5.0"
 description = "A list-like structure which implements collections.abc.MutableSequence"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5b6a66c18b5b9dd261ca98dffcb826a525334b2f29e7caa54e182255c5f6a65a"},
     {file = "frozenlist-1.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d1b3eb7b05ea246510b43a7e53ed1653e55c2121019a97e60cad7efb881a97bb"},
@@ -721,7 +723,7 @@ version = "2025.2.0"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "fsspec-2025.2.0-py3-none-any.whl", hash = "sha256:9de2ad9ce1f85e1931858535bc882543171d197001a0a5eb2ddc04f1781ab95b"},
     {file = "fsspec-2025.2.0.tar.gz", hash = "sha256:1c24b16eaa0a1798afa0337aa0db9b256718ab2a89c425371f5628d22c3b6afd"},
@@ -968,7 +970,7 @@ version = "0.28.1"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "huggingface_hub-0.28.1-py3-none-any.whl", hash = "sha256:aa6b9a3ffdae939b72c464dbb0d7f99f56e649b55c3d52406f49e0a5a620c0a7"},
     {file = "huggingface_hub-0.28.1.tar.gz", hash = "sha256:893471090c98e3b6efbdfdacafe4052b20b84d59866fb6f54c33d9af18c303ae"},
@@ -1003,7 +1005,7 @@ version = "10.0"
 description = "Human friendly output for text interfaces using Python"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "humanfriendly-10.0-py2.py3-none-any.whl", hash = "sha256:1697e1a8a8f550fd43c2865cd84542fc175a61dcb779b6fee18cf6b6ccba1477"},
     {file = "humanfriendly-10.0.tar.gz", hash = "sha256:6b0b831ce8f15f7300721aa49829fc4e83921a9a301cc7f606be6686a2288ddc"},
@@ -1023,6 +1025,7 @@ files = [
     {file = "idna-3.10-py3-none-any.whl", hash = "sha256:946d195a0d259cbba61165e88e65941f16e9b36ea6ddb97f00452bae8b1287d3"},
     {file = "idna-3.10.tar.gz", hash = "sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9"},
 ]
+markers = {main = "platform_machine == \"x86_64\" or platform_machine == \"arm64\""}
 
 [package.extras]
 all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2)"]
@@ -1410,7 +1413,7 @@ version = "1.3.0"
 description = "Python library for arbitrary-precision floating-point arithmetic"
 optional = false
 python-versions = "*"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "mpmath-1.3.0-py3-none-any.whl", hash = "sha256:a0b2b9fe80bbcd81a6647ff13108738cfb482d481d826cc0e02f5b35e5c88d2c"},
     {file = "mpmath-1.3.0.tar.gz", hash = "sha256:7a28eb2a9774d00c7bc92411c19a89209d5da7c4c9a9e227be8330a23a25b91f"},
@@ -1502,7 +1505,7 @@ version = "6.1.0"
 description = "multidict implementation"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "multidict-6.1.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3380252550e372e8511d49481bd836264c009adb826b23fefcc5dd3c69692f60"},
     {file = "multidict-6.1.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:99f826cbf970077383d7de805c0681799491cb939c25450b9b5b3ced03ca99f1"},
@@ -1607,7 +1610,7 @@ version = "0.70.15"
 description = "better multiprocessing and multithreading in Python"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "multiprocess-0.70.15-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:aa36c7ed16f508091438687fe9baa393a7a8e206731d321e443745e743a0d4e5"},
     {file = "multiprocess-0.70.15-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:20e024018c46d0d1602024c613007ac948f9754659e3853b0aa705e83f6931d8"},
@@ -1866,53 +1869,6 @@ files = [
     {file = "opt_einsum-3.4.0.tar.gz", hash = "sha256:96ca72f1b886d148241348783498194c577fa30a8faac108586b14f1ba4473ac"},
 ]
 
-[[package]]
-name = "optimum"
-version = "1.23.3"
-description = "Optimum Library is an extension of the Hugging Face Transformers library, providing a framework to integrate third-party libraries from Hardware Partners and interface with their specific functionality."
-optional = false
-python-versions = ">=3.7.0"
-groups = ["main"]
-files = [
-    {file = "optimum-1.23.3-py3-none-any.whl", hash = "sha256:ac34b497310e74e919e8eb3bc01cfea48bca304ade3e3ce8a7707d125120001a"},
-    {file = "optimum-1.23.3.tar.gz", hash = "sha256:2089bd73d1232686473a80effd53800f8a8c385c02126e80d35c07227c1b9bf5"},
-]
-
-[package.dependencies]
-coloredlogs = "*"
-datasets = "*"
-huggingface-hub = ">=0.8.0"
-numpy = "*"
-packaging = "*"
-sympy = "*"
-torch = ">=1.11"
-transformers = ">=4.29"
-
-[package.extras]
-amd = ["optimum-amd"]
-benchmark = ["evaluate (>=0.2.0)", "optuna", "scikit-learn", "seqeval", "torchvision", "tqdm"]
-dev = ["Pillow", "accelerate", "black (>=23.1,<24.0)", "diffusers (>=0.17.0)", "einops", "parameterized", "pytest (<=8.0.0)", "pytest-xdist", "requests", "rjieba", "ruff (==0.1.5)", "sacremoses", "scikit-learn", "sentencepiece", "timm", "torchaudio", "torchvision"]
-diffusers = ["diffusers"]
-doc-build = ["accelerate"]
-exporters = ["onnx", "onnxruntime", "timm", "transformers (<4.47.0)"]
-exporters-gpu = ["onnx", "onnxruntime-gpu", "timm", "transformers (<4.47.0)"]
-exporters-tf = ["datasets (<=2.16)", "h5py", "numpy (<1.24.0)", "onnx", "onnxruntime", "tensorflow (>=2.4,<=2.12.1)", "tf2onnx", "timm", "transformers (>=4.26,<4.38)"]
-furiosa = ["optimum-furiosa"]
-graphcore = ["optimum-graphcore"]
-habana = ["optimum-habana", "transformers (>=4.45.0,<4.46.0)"]
-intel = ["optimum-intel (>=1.18.0)"]
-ipex = ["optimum-intel[ipex] (>=1.18.0)"]
-neural-compressor = ["optimum-intel[neural-compressor] (>=1.18.0)"]
-neuron = ["optimum-neuron[neuron] (>=0.0.20)", "transformers (>=4.36.2,<4.42.0)"]
-neuronx = ["optimum-neuron[neuronx] (>=0.0.20)", "transformers (>=4.36.2,<4.42.0)"]
-nncf = ["optimum-intel[nncf] (>=1.18.0)"]
-onnxruntime = ["datasets (>=1.2.1)", "evaluate", "onnx", "onnxruntime (>=1.11.0)", "protobuf (>=3.20.1)", "transformers (<4.47.0)"]
-onnxruntime-gpu = ["accelerate", "datasets (>=1.2.1)", "evaluate", "onnx", "onnxruntime-gpu (>=1.11.0)", "protobuf (>=3.20.1)", "transformers (<4.47.0)"]
-openvino = ["optimum-intel[openvino] (>=1.18.0)"]
-quality = ["black (>=23.1,<24.0)", "ruff (==0.1.5)"]
-quanto = ["optimum-quanto (>=0.2.4)"]
-tests = ["Pillow", "accelerate", "diffusers (>=0.17.0)", "einops", "parameterized", "pytest (<=8.0.0)", "pytest-xdist", "requests", "rjieba", "sacremoses", "scikit-learn", "sentencepiece", "timm", "torchaudio", "torchvision"]
-
 [[package]]
 name = "packaging"
 version = "24.2"
@@ -1924,6 +1880,7 @@ files = [
     {file = "packaging-24.2-py3-none-any.whl", hash = "sha256:09abb1bccd265c01f4a3aa3f7a7db064b36514d2cba19a2f694fe6150451a759"},
     {file = "packaging-24.2.tar.gz", hash = "sha256:c228a6dc5e932d346bc5739379109d49e8853dd8223571c7c5b55260edc0b97f"},
 ]
+markers = {main = "platform_machine == \"x86_64\" or platform_machine == \"arm64\""}
 
 [[package]]
 name = "pandas"
@@ -1931,7 +1888,7 @@ version = "2.0.3"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "pandas-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e4c7c9f27a4185304c7caf96dc7d91bc60bc162221152de697c98eb0b2648dd8"},
     {file = "pandas-2.0.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f167beed68918d62bffb6ec64f2e1d8a7d297a038f86d4aed056b9493fca407f"},
@@ -2171,7 +2128,7 @@ version = "0.2.0"
 description = "Accelerated property cache"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "propcache-0.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c5869b8fd70b81835a6f187c5fdbe67917a04d7e52b6e7cc4e5fe39d55c39d58"},
     {file = "propcache-0.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:952e0d9d07609d9c5be361f33b0d6d650cd2bae393aabb11d9b719364521984b"},
@@ -2369,7 +2326,7 @@ version = "17.0.0"
 description = "Python library for Apache Arrow"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "pyarrow-17.0.0-cp310-cp310-macosx_10_15_x86_64.whl", hash = "sha256:a5c8b238d47e48812ee577ee20c9a2779e6a5904f1708ae240f53ecbee7c9f07"},
     {file = "pyarrow-17.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:db023dc4c6cae1015de9e198d41250688383c3f9af8f565370ab2b4cb5f62655"},
@@ -2462,7 +2419,7 @@ version = "3.5.4"
 description = "A python implementation of GNU readline."
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 markers = "sys_platform == \"win32\""
 files = [
     {file = "pyreadline3-3.5.4-py3-none-any.whl", hash = "sha256:eaf8e6cc3c49bcccf145fc6067ba8643d1df34d604a1ec0eccbf7a18e6d3fae6"},
@@ -2516,7 +2473,7 @@ version = "2025.1"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "pytz-2025.1-py2.py3-none-any.whl", hash = "sha256:89dd22dca55b46eac6eda23b2d72721bf1bdfef212645d81513ef5d03038de57"},
     {file = "pytz-2025.1.tar.gz", hash = "sha256:c2db42be2a2518b28e65f9207c4d05e6ff547d1efa4086469ef855e4ab70178e"},
@@ -2620,7 +2577,7 @@ version = "2024.11.6"
 description = "Alternative regular expression module, to replace re."
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91"},
     {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0"},
@@ -2729,6 +2686,7 @@ files = [
     {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
     {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
 ]
+markers = {main = "platform_machine == \"x86_64\" or platform_machine == \"arm64\""}
 
 [package.dependencies]
 certifi = ">=2017.4.17"
@@ -2800,7 +2758,7 @@ version = "0.5.2"
 description = ""
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "safetensors-0.5.2-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:45b6092997ceb8aa3801693781a71a99909ab9cc776fbc3fa9322d29b1d3bef2"},
     {file = "safetensors-0.5.2-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:6d0d6a8ee2215a440e1296b843edf44fd377b055ba350eaba74655a2fe2c4bae"},
@@ -3084,7 +3042,7 @@ version = "1.13.3"
 description = "Computer algebra system (CAS) in Python"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "sympy-1.13.3-py3-none-any.whl", hash = "sha256:54612cf55a62755ee71824ce692986f23c88ffa77207b30c1368eda4a7060f73"},
     {file = "sympy-1.13.3.tar.gz", hash = "sha256:b27fd2c6530e0ab39e275fc9b683895367e51d5da91baa8d3d64db2565fec4d9"},
@@ -3380,7 +3338,7 @@ version = "0.20.3"
 description = ""
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "tokenizers-0.20.3-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:31ccab28dbb1a9fe539787210b0026e22debeab1662970f61c2d921f7557f7e4"},
     {file = "tokenizers-0.20.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c6361191f762bda98c773da418cf511cbaa0cb8d0a1196f16f8c0119bde68ff8"},
@@ -3552,7 +3510,7 @@ version = "1.12.1"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = false
 python-versions = ">=3.7.0"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "torch-1.12.1-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:9c038662db894a23e49e385df13d47b2a777ffd56d9bcd5b832593fab0a7e286"},
     {file = "torch-1.12.1-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:4e1b9c14cf13fd2ab8d769529050629a0e68a6fc5cb8e84b4a3cc1dd8c4fe541"},
@@ -3646,7 +3604,7 @@ version = "4.46.3"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = false
 python-versions = ">=3.8.0"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "transformers-4.46.3-py3-none-any.whl", hash = "sha256:a12ef6f52841fd190a3e5602145b542d03507222f2c64ebb7ee92e8788093aef"},
     {file = "transformers-4.46.3.tar.gz", hash = "sha256:8ee4b3ae943fe33e82afff8e837f4b052058b07ca9be3cb5b729ed31295f72cc"},
@@ -3753,7 +3711,7 @@ version = "2025.1"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "tzdata-2025.1-py2.py3-none-any.whl", hash = "sha256:7e127113816800496f027041c570f50bcd464a020098a3b6b199517772303639"},
     {file = "tzdata-2025.1.tar.gz", hash = "sha256:24894909e88cdb28bd1636c6887801df64cb485bd593f2fd83ef29075a81d694"},
@@ -3914,7 +3872,7 @@ version = "3.5.0"
 description = "Python binding for xxHash"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "xxhash-3.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ece616532c499ee9afbb83078b1b952beffef121d989841f7f4b3dc5ac0fd212"},
     {file = "xxhash-3.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3171f693dbc2cef6477054a665dc255d996646b4023fe56cb4db80e26f4cc520"},
@@ -4063,7 +4021,7 @@ version = "1.15.2"
 description = "Yet another URL library"
 optional = false
 python-versions = ">=3.8"
-groups = ["main", "dev"]
+groups = ["dev"]
 files = [
     {file = "yarl-1.15.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e4ee8b8639070ff246ad3649294336b06db37a94bdea0d09ea491603e0be73b8"},
     {file = "yarl-1.15.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a7cf963a357c5f00cb55b1955df8bbe68d2f2f65de065160a1c26b85a1e44172"},
@@ -4194,4 +4152,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.8, <3.11"
-content-hash = "f40eb267f2073255d1a5753db4ec40bf91f459bf1b83140f4a63b89d17c13eb8"
+content-hash = "732146f5dfc8becf5f8ab348e666483456792ff1d127555f703768260a01d63b"
diff --git a/pyproject.toml b/pyproject.toml
index ca84608e..4f215a77 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "onnx2kerastl"
-version = "0.0.165"
+version = "0.0.168"
 description = ""
 authors = ["dorhar <doron.harnoy@tensorleap.ai>"]
 license = "MIT"
@@ -17,7 +17,6 @@ fvcore = "^0.1.5.post20221221"
 boto3 = "^1.24.22"
 tensorflow-io-gcs-filesystem = "0.34.0"
 keras-data-format-converter = "0.1.22"
-optimum = "1.23.3"
 
 [tool.poetry.dev-dependencies]
 pytest = "^7.1.2"
diff --git a/test/models/private_tests/test_dinov2.py b/test/models/private_tests/test_dinov2.py
new file mode 100644
index 00000000..1498d4b5
--- /dev/null
+++ b/test/models/private_tests/test_dinov2.py
@@ -0,0 +1,34 @@
+import numpy as np
+import onnx
+from onnx2kerastl import onnx_to_keras
+from keras_data_format_converter import convert_channels_first_to_last
+import onnxruntime as ort
+import torch
+import pytest
+from test.models.private_tests.aws_utils import aws_s3_download
+
+
+@pytest.mark.parametrize('aws_s3_download', [["dinov2/", "dinov2/", False]], indirect=True)
+def test_dinov2(aws_s3_download):
+    # This is commented out in case we'll upgrade python
+    # batch_size = 1
+    # dinov2_vits14 = torch.hub.load('facebookresearch/dinov2', 'dinov2_vits14')
+    # wm = wrapper_model(dinov2_vits14).to('cpu')
+    # wm.eval()
+    # dummy_input = torch.FloatTensor(np.random.uniform(0, 1, (batch_size, 3, 224, 224)))
+    # torch.onnx.export(wm, dummy_input, "dino-2-test.onnx", input_names=['img'],
+    #                   output_names=['vit_out'])
+    np_input = list(np.random.rand(1, 3, 224, 224))
+    onnx_path = f'{aws_s3_download}/dino-2-test.onnx'
+    onnx_model = onnx.load(onnx_path)
+    keras_model = onnx_to_keras(onnx_model, ['img', 'masks'], allow_partial_compilation=False)
+    flipped_model = convert_channels_first_to_last(keras_model.converted_model, should_transform_inputs_and_outputs=False)
+    ort_session = ort.InferenceSession(onnx_path)
+    keras_res = flipped_model(np.array(np_input))
+    res = ort_session.run(
+        ['vit_out'],
+        input_feed={"img": np.array(np_input).astype(np.float32)}
+    )
+    t_mean, t_max = (res[0]-keras_res).__abs__().numpy().mean(), (res[0]-keras_res).__abs__().numpy().max()
+    assert t_mean < 5e-2
+    assert t_max < 0.4
diff --git a/test/models/test_dinov2.py b/test/models/test_dinov2.py
deleted file mode 100644
index 32f0e4ef..00000000
--- a/test/models/test_dinov2.py
+++ /dev/null
@@ -1,39 +0,0 @@
-import numpy as np
-import onnx
-from onnx2kerastl import onnx_to_keras
-from keras_data_format_converter import convert_channels_first_to_last
-import onnxruntime as ort
-import torch
-
-
-class wrapper_model(torch.nn.Module):
-    def __init__(self, model):
-        super().__init__()
-        self.inner_model = model
-
-    def forward(self, tensor):
-        ff = self.inner_model(tensor)
-        return ff
-
-
-def test_dinov2():
-    batch_size = 1
-    dinov2_vits14 = torch.hub.load('facebookresearch/dinov2', 'dinov2_vits14')
-    wm = wrapper_model(dinov2_vits14).to('cpu')
-    wm.eval()
-    dummy_input = torch.FloatTensor(np.random.uniform(0, 1, (batch_size, 3, 224, 224)))
-    torch.onnx.export(wm, dummy_input, "dino-2-test.onnx", input_names=['img'],
-                      output_names=['vit_out'])
-    np_input = list(np.random.rand(1, 3, 224, 224))
-    onnx_model = onnx.load('dino-2-test.onnx')
-    keras_model = onnx_to_keras(onnx_model, ['img', 'masks'], allow_partial_compilation=False)
-    flipped_model = convert_channels_first_to_last(keras_model.converted_model, should_transform_inputs_and_outputs=False)
-    ort_session = ort.InferenceSession('dino-2-test.onnx')
-    keras_res = flipped_model(np.array(np_input))
-    res = ort_session.run(
-        ['vit_out'],
-        input_feed={"img": np.array(np_input).astype(np.float32)}
-    )
-    t_mean, t_max = (res[0]-keras_res).__abs__().numpy().mean(), (res[0]-keras_res).__abs__().numpy().max()
-    assert t_mean < 5e-2
-    assert t_max < 0.4
diff --git a/test/models/test_llama_sentiment_analysis.py b/test/models/test_llama_sentiment_analysis.py
index ffec36f1..addfd247 100644
--- a/test/models/test_llama_sentiment_analysis.py
+++ b/test/models/test_llama_sentiment_analysis.py
@@ -8,7 +8,7 @@
 from onnx2kerastl import onnx_to_keras
 from keras_data_format_converter import convert_channels_first_to_last
 from onnx2kerastl.customonnxlayer import onnx_custom_objects_map
-from test.utils import export_torch_to_onnx_optimum
+#from test.utils import export_torch_to_onnx_optimum
 
 
 @pytest.mark.skip(reason="Fails on CI but works locally (might be too big?)")
diff --git a/test/utils.py b/test/utils.py
index f04fff55..b2a4d387 100644
--- a/test/utils.py
+++ b/test/utils.py
@@ -7,7 +7,7 @@
 
 from onnx2kerastl import onnx_to_keras
 from onnx2kerastl.utils import check_torch_keras_error
-from optimum.exporters.onnx import main_export
+#from optimum.exporters.onnx import main_export
 
 NP_SEED = 42
 
@@ -58,31 +58,31 @@ def is_lambda_layers_exist(model: Model):
     return any(isinstance(layer, Lambda) for layer in model.layers)
 
 
-def export_torch_to_onnx_optimum(model_name: str, model_output_path: str, task="causal-lm"):
-    """
-    this function get a model as an input (Hugginface or local path), creates a folder and save the onnx model as output.
-    it uses the optimum library.
-    NOTE: For llama model the maximum absolute difference of the logits larget than 1e-5, it shouldnt be that important!
-    Args:
-        model_name: model path (local or HF name)
-        model_output_name: output folder path
-        task: model task
-
-    Returns:
-        creates the onnx model in the output folder path
-    """
-    main_export(
-        model_name_or_path=model_name,
-        task=task,
-        output=model_output_path,
-        opset=None,
-        device="cpu",
-        dtype=None,
-        pad_token_id=None,
-        trust_remote_code=False,
-        do_validation=True,
-        framework=None,
-        no_post_process=False,
-        model_kwargs=None,
-        atol = 1e-5
-    )
\ No newline at end of file
+# def export_torch_to_onnx_optimum(model_name: str, model_output_path: str, task="causal-lm"):
+#     """
+#     this function get a model as an input (Hugginface or local path), creates a folder and save the onnx model as output.
+#     it uses the optimum library.
+#     NOTE: For llama model the maximum absolute difference of the logits larget than 1e-5, it shouldnt be that important!
+#     Args:
+#         model_name: model path (local or HF name)
+#         model_output_name: output folder path
+#         task: model task
+#
+#     Returns:
+#         creates the onnx model in the output folder path
+#     """
+#     main_export(
+#         model_name_or_path=model_name,
+#         task=task,
+#         output=model_output_path,
+#         opset=None,
+#         device="cpu",
+#         dtype=None,
+#         pad_token_id=None,
+#         trust_remote_code=False,
+#         do_validation=True,
+#         framework=None,
+#         no_post_process=False,
+#         model_kwargs=None,
+#         atol = 1e-5
+#     )
\ No newline at end of file