diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
new file mode 100644
index 00000000..a412f02e
--- /dev/null
+++ b/.github/workflows/release.yml
@@ -0,0 +1,33 @@
+name: PyPI release
+
+on:
+  push:
+    branches: [main]
+
+defaults:
+  run:
+    shell: bash
+
+jobs:
+  publish-to-pypi:
+    name: Publish to PyPI
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest]
+        python-version: ["3.10"]
+    timeout-minutes: 60
+    environment:
+      name: pypi
+      url: https://pypi.org/p/quadra
+    permissions:
+      id-token: write # IMPORTANT: mandatory for trusted publishing
+    steps:
+      - uses: actions/checkout@v3
+      - name: Build distribution 📦
+        run: |
+          curl -sSL https://install.python-poetry.org | python3 -
+          poetry build
+      - name: Publish distribution 📦 to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5b753d1a..7a22117c 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -2,8 +2,22 @@
 # Changelog
 All notable changes to this project will be documented in this file.
 
+### [2.2.1]
+
+#### Updated
+
+- Update anomalib version, improve release workflow
+
+### [2.2.0]
+
+#### Updated
+
+- Update dependencies to support publishing Quadra to PyPI
+
 ### [2.1.13]
 
+#### Updated
+
 - Improve safe batch size computation for sklearn based classification tasks
 
 ### [2.1.12]
diff --git a/README.md b/README.md
index c857b785..af9e3928 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 <h1></h1>
 <p align="center">
-  <img src="docs/images/quadra_text_logo.png" alt="Quadra Logo" width="100%">
+  <img src="https://github.com/orobix/quadra/raw/main/docs/images/quadra_text_logo.png" alt="Quadra Logo" width="100%">
 </p>
 
 <p align="center">
@@ -20,7 +20,7 @@
     alt="pre-commit"
   /></a>
   <a href="https://github.com/econchick/interrogate"><img
-    src="docs/images/interrogate_badge.svg"
+    src="https://github.com/orobix/quadra/raw/main/docs/images/interrogate_badge.svg"
     alt="interrogate"
   /></a>
   <a href="https://github.com/PyCQA/pylint"><img
@@ -42,16 +42,14 @@ ______________________________________________________________________
 
 ## Quick Start Guide
 
-Currently we support installing from source since the library is not yet available on `PyPI` and currently supported Python versions are `3.9` and `3.10`.
-
-If you use pip to manage your packages, you can install `quadra` from source by running the following command:
+If you use pip to manage your packages, you can install `quadra` from PyPi by running the following command:
 ```shell
-pip install git+https://github.com/orobix/quadra.git
+pip install quadra
 ```
 
-If instead you prefer to use poetry, you can install `quadra` from source by running the following command:
+If instead you prefer to use poetry, you can install `quadra` from PyPi by running the following command:
 ```shell
-poetry add git+https://github.com/orobix/quadra.git
+poetry add quadra
 ```
 
 If you don't have virtual environment ready, Let's set up our environment for using the `quadra` library. We have two parts in this guide: Common setup and Environment-specific setup.
@@ -92,13 +90,13 @@ source myenv/bin/activate
 
     * **Install the `quadra` package** with pip:
       ```shell
-      pip install git+https://github.com/orobix/quadra.git
+      pip install quadra
       ```
 
     * **Install the `quadra` package** with poetry:
       ```shell
       curl -sSL https://install.python-poetry.org | python3 -
-      poetry add git+https://github.com/orobix/quadra.git
+      poetry add quadra
       ```
 
 4. **Run from CLI**:
diff --git a/poetry.lock b/poetry.lock
index fa4da03e..b8f0edc8 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -186,37 +186,27 @@ six = ">=1.5"
 test = ["flake8 (==3.7.9)", "mock (==2.0.0)", "pylint (==1.9.3)"]
 
 [[package]]
-name = "anomalib"
-version = "0.7.0+obx.1.3.3"
-description = "anomalib - Anomaly Detection Library"
+name = "anomalib-orobix"
+version = "0.7.0.dev140"
+description = "Orobix anomalib fork"
 optional = false
-python-versions = ">=3.7"
-files = []
-develop = false
+python-versions = ">=3.9,<3.11"
+files = [
+    {file = "anomalib_orobix-0.7.0.dev140-py3-none-any.whl", hash = "sha256:4d78ab39fd38c88214b89edd6eccb3f66f91e5771f9f6382e4140bb348ac9ac9"},
+    {file = "anomalib_orobix-0.7.0.dev140.tar.gz", hash = "sha256:e9c6d3a1c4547366d7622295080ab85710a381831f6b7d0a29dd03ae061a656d"},
+]
 
 [package.dependencies]
-einops = "==0.6.*"
-freia = "==0.2.*"
+einops = ">=0.6,<0.7"
+freia = ">=0.2,<0.3"
 gradio = "3.0.2"
 imgaug = "0.4.0"
 jsonargparse = {version = ">=4.3.0,<4.4.0", extras = ["signatures"]}
 kornia = "0.6.5"
 line-profiler = "3.5.1"
-omegaconf = "==2.3.*"
+omegaconf = ">=2.3,<2.4"
 wandb = "0.12.17"
 
-[package.extras]
-full = ["GitPython", "comet-ml (>=3.31.7)", "defusedxml (==0.7.1)", "gitpython", "gradio (>=2.9.4)", "ipykernel", "ipykernel", "ipywidgets", "networkx (>=2.5,<3.0)", "nncf (>=2.1.0)", "notebook", "onnx (>=1.10.1)", "openvino-dev (>=2022.3.0)", "requests (>=2.26.0)", "tensorboard", "wandb (==0.12.17)"]
-loggers = ["GitPython", "comet-ml (>=3.31.7)", "gradio (>=2.9.4)", "ipykernel", "tensorboard", "wandb (==0.12.17)"]
-notebooks = ["gitpython", "ipykernel", "ipywidgets", "notebook"]
-openvino = ["defusedxml (==0.7.1)", "networkx (>=2.5,<3.0)", "nncf (>=2.1.0)", "onnx (>=1.10.1)", "openvino-dev (>=2022.3.0)", "requests (>=2.26.0)"]
-
-[package.source]
-type = "git"
-url = "https://github.com/orobix/anomalib.git"
-reference = "v0.7.0+obx.1.3.3"
-resolved_reference = "02953d367168659ad9324ca03a9fa9c63aa69dbe"
-
 [[package]]
 name = "antlr4-python3-runtime"
 version = "4.9.3"
@@ -3430,115 +3420,6 @@ files = [
     {file = "numpy-1.26.3.tar.gz", hash = "sha256:697df43e2b6310ecc9d95f05d5ef20eacc09c7c4ecc9da3f235d39e71b7da1e4"},
 ]
 
-[[package]]
-name = "nvidia-cublas-cu12"
-version = "12.1.3.1"
-description = "CUBLAS native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:ee53ccca76a6fc08fb9701aa95b6ceb242cdaab118c3bb152af4e579af792728"},
-    {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-win_amd64.whl", hash = "sha256:2b964d60e8cf11b5e1073d179d85fa340c120e99b3067558f3cf98dd69d02906"},
-]
-
-[[package]]
-name = "nvidia-cuda-cupti-cu12"
-version = "12.1.105"
-description = "CUDA profiling tools runtime libs."
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:e54fde3983165c624cb79254ae9818a456eb6e87a7fd4d56a2352c24ee542d7e"},
-    {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:bea8236d13a0ac7190bd2919c3e8e6ce1e402104276e6f9694479e48bb0eb2a4"},
-]
-
-[[package]]
-name = "nvidia-cuda-nvrtc-cu12"
-version = "12.1.105"
-description = "NVRTC native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:339b385f50c309763ca65456ec75e17bbefcbbf2893f462cb8b90584cd27a1c2"},
-    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:0a98a522d9ff138b96c010a65e145dc1b4850e9ecb75a0172371793752fd46ed"},
-]
-
-[[package]]
-name = "nvidia-cuda-runtime-cu12"
-version = "12.1.105"
-description = "CUDA Runtime native Libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:6e258468ddf5796e25f1dc591a31029fa317d97a0a94ed93468fc86301d61e40"},
-    {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:dfb46ef84d73fababab44cf03e3b83f80700d27ca300e537f85f636fac474344"},
-]
-
-[[package]]
-name = "nvidia-cudnn-cu12"
-version = "8.9.2.26"
-description = "cuDNN runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl", hash = "sha256:5ccb288774fdfb07a7e7025ffec286971c06d8d7b4fb162525334616d7629ff9"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu12 = "*"
-
-[[package]]
-name = "nvidia-cufft-cu12"
-version = "11.0.2.54"
-description = "CUFFT native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl", hash = "sha256:794e3948a1aa71fd817c3775866943936774d1c14e7628c74f6f7417224cdf56"},
-    {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-win_amd64.whl", hash = "sha256:d9ac353f78ff89951da4af698f80870b1534ed69993f10a4cf1d96f21357e253"},
-]
-
-[[package]]
-name = "nvidia-curand-cu12"
-version = "10.3.2.106"
-description = "CURAND native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:9d264c5036dde4e64f1de8c50ae753237c12e0b1348738169cd0f8a536c0e1e0"},
-    {file = "nvidia_curand_cu12-10.3.2.106-py3-none-win_amd64.whl", hash = "sha256:75b6b0c574c0037839121317e17fd01f8a69fd2ef8e25853d826fec30bdba74a"},
-]
-
-[[package]]
-name = "nvidia-cusolver-cu12"
-version = "11.4.5.107"
-description = "CUDA solver native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd"},
-    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-win_amd64.whl", hash = "sha256:74e0c3a24c78612192a74fcd90dd117f1cf21dea4822e66d89e8ea80e3cd2da5"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu12 = "*"
-nvidia-cusparse-cu12 = "*"
-nvidia-nvjitlink-cu12 = "*"
-
-[[package]]
-name = "nvidia-cusparse-cu12"
-version = "12.1.0.106"
-description = "CUSPARSE native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c"},
-    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-win_amd64.whl", hash = "sha256:b798237e81b9719373e8fae8d4f091b70a0cf09d9d85c95a557e11df2d8e9a5a"},
-]
-
-[package.dependencies]
-nvidia-nvjitlink-cu12 = "*"
-
 [[package]]
 name = "nvidia-ml-py"
 version = "11.515.75"
@@ -3550,38 +3431,6 @@ files = [
     {file = "nvidia_ml_py-11.515.75-py3-none-any.whl", hash = "sha256:5bf5f5240f5a242689c1d1129135a0bd79c8b93d2a282c7229fe32ab63e7999b"},
 ]
 
-[[package]]
-name = "nvidia-nccl-cu12"
-version = "2.18.1"
-description = "NVIDIA Collective Communication Library (NCCL) Runtime"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nccl_cu12-2.18.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:1a6c4acefcbebfa6de320f412bf7866de856e786e0462326ba1bac40de0b5e71"},
-]
-
-[[package]]
-name = "nvidia-nvjitlink-cu12"
-version = "12.3.101"
-description = "Nvidia JIT LTO Library"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:64335a8088e2b9d196ae8665430bc6a2b7e6ef2eb877a9c735c804bd4ff6467c"},
-    {file = "nvidia_nvjitlink_cu12-12.3.101-py3-none-win_amd64.whl", hash = "sha256:1b2e317e437433753530792f13eece58f0aec21a2b05903be7bffe58a606cbd1"},
-]
-
-[[package]]
-name = "nvidia-nvtx-cu12"
-version = "12.1.105"
-description = "NVIDIA Tools Extension"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5"},
-    {file = "nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82"},
-]
-
 [[package]]
 name = "nvitop"
 version = "0.11.0"
@@ -3778,9 +3627,9 @@ files = [
 
 [package.dependencies]
 numpy = [
+    {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\""},
     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\""},
-    {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
 ]
 
@@ -3802,9 +3651,9 @@ files = [
 
 [package.dependencies]
 numpy = [
+    {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\""},
     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\""},
-    {version = ">=1.21.0", markers = "python_version == \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
     {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
 ]
 
@@ -3961,8 +3810,8 @@ files = [
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
     {version = ">=1.20.3", markers = "python_version < \"3.10\""},
+    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
 ]
 python-dateutil = ">=2.8.1"
 pytz = ">=2020.1"
@@ -5376,31 +5225,21 @@ cryptography = ">=2.0"
 jeepney = ">=0.6"
 
 [[package]]
-name = "segmentation_models_pytorch"
-version = "0.3.3"
-description = "Image segmentation models with pre-trained backbones. PyTorch."
+name = "segmentation-models-pytorch-orobix"
+version = "0.3.3.dev1"
+description = "Deep Learning experiment orchestration library"
 optional = false
-python-versions = ">=3.7.0"
-files = []
-develop = false
+python-versions = ">=3.9,<3.11"
+files = [
+    {file = "segmentation_models_pytorch_orobix-0.3.3.dev1-py3-none-any.whl", hash = "sha256:e64ac97161fecb12af51f073c24b3a74c0f6ef37e39a756f7e846340ab3156a8"},
+    {file = "segmentation_models_pytorch_orobix-0.3.3.dev1.tar.gz", hash = "sha256:291d3d36c84cefd9af3b31be2c49b494bf36385b2da77353642344168b979025"},
+]
 
 [package.dependencies]
 efficientnet-pytorch = "0.7.1"
-pillow = "*"
 pretrainedmodels = "0.7.4"
-six = "*"
-timm = "0.9.12"
+timm = ">=0.9.12,<0.10.0"
 torchvision = ">=0.5.0"
-tqdm = "*"
-
-[package.extras]
-test = ["black (==22.3.0)", "flake8 (==4.0.1)", "flake8-docstrings (==1.6.0)", "mock", "pre-commit", "pytest"]
-
-[package.source]
-type = "git"
-url = "https://github.com/qubvel/segmentation_models.pytorch"
-reference = "7b381f899ed472a477a89d381689caf535b5d0a6"
-resolved_reference = "7b381f899ed472a477a89d381689caf535b5d0a6"
 
 [[package]]
 name = "sentry-sdk"
@@ -5993,96 +5832,12 @@ optional = false
 python-versions = ">=3.8.0"
 files = [
     {file = "torch-2.1.2+cu121-cp310-cp310-linux_x86_64.whl", hash = "sha256:b2184b7729ef3b9b10065c074a37c1e603fd99f91e38376e25cb7ed6e1d54696"},
-]
-
-[package.dependencies]
-filelock = "*"
-fsspec = "*"
-jinja2 = "*"
-networkx = "*"
-sympy = "*"
-triton = {version = "2.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-typing-extensions = "*"
-
-[package.extras]
-dynamo = ["jinja2"]
-opt-einsum = ["opt-einsum (>=3.3)"]
-
-[package.source]
-type = "url"
-url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp310-cp310-linux_x86_64.whl"
-
-[[package]]
-name = "torch"
-version = "2.1.2+cu121"
-description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
-optional = false
-python-versions = ">=3.8.0"
-files = [
     {file = "torch-2.1.2+cu121-cp310-cp310-win_amd64.whl", hash = "sha256:9925143dece0e63c5404a72d59eb668ef78795418e96b576f94d75dcea6030b9"},
-]
-
-[package.dependencies]
-filelock = "*"
-fsspec = "*"
-jinja2 = "*"
-networkx = "*"
-nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.18.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-sympy = "*"
-triton = {version = "2.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-typing-extensions = "*"
-
-[package.extras]
-opt-einsum = ["opt-einsum (>=3.3)"]
-
-[package.source]
-type = "url"
-url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp310-cp310-win_amd64.whl"
-
-[[package]]
-name = "torch"
-version = "2.1.2+cu121"
-description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
-optional = false
-python-versions = ">=3.8.0"
-files = [
+    {file = "torch-2.1.2+cu121-cp311-cp311-linux_x86_64.whl", hash = "sha256:ca05cae9334504d1903e16c50ddf045329a859d5b1a27ed2dc1d58ed066df6fa"},
+    {file = "torch-2.1.2+cu121-cp311-cp311-win_amd64.whl", hash = "sha256:c92e9c559a82466fc5989f648807d2c0215bcce09b97ad7a20d038b686783229"},
+    {file = "torch-2.1.2+cu121-cp38-cp38-linux_x86_64.whl", hash = "sha256:daa179bb558f78f2165db974a6744ec8de2ea71eb6aaf362bdae7616012c0302"},
+    {file = "torch-2.1.2+cu121-cp38-cp38-win_amd64.whl", hash = "sha256:44c31fc1e470428682e212473507116ec3afa583d6b79d92858bf3dc24b334ea"},
     {file = "torch-2.1.2+cu121-cp39-cp39-linux_x86_64.whl", hash = "sha256:eaaf6907e3723c0ca6a91df5e01a7eef8cabec93120e9a50739f5a5f14a2aa46"},
-]
-
-[package.dependencies]
-filelock = "*"
-fsspec = "*"
-jinja2 = "*"
-networkx = "*"
-sympy = "*"
-triton = {version = "2.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-typing-extensions = "*"
-
-[package.extras]
-dynamo = ["jinja2"]
-opt-einsum = ["opt-einsum (>=3.3)"]
-
-[package.source]
-type = "url"
-url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp39-cp39-linux_x86_64.whl"
-
-[[package]]
-name = "torch"
-version = "2.1.2+cu121"
-description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
-optional = false
-python-versions = ">=3.8.0"
-files = [
     {file = "torch-2.1.2+cu121-cp39-cp39-win_amd64.whl", hash = "sha256:2d287804328dfb950ae6d418c9d8561d8f379237cf0710566d80efb96b6cd744"},
 ]
 
@@ -6091,27 +5846,18 @@ filelock = "*"
 fsspec = "*"
 jinja2 = "*"
 networkx = "*"
-nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.18.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
 triton = {version = "2.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 typing-extensions = "*"
 
 [package.extras]
+dynamo = ["jinja2"]
 opt-einsum = ["opt-einsum (>=3.3)"]
 
 [package.source]
-type = "url"
-url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp39-cp39-win_amd64.whl"
+type = "legacy"
+url = "https://download.pytorch.org/whl/cu121"
+reference = "torch_cu121"
 
 [[package]]
 name = "torchinfo"
@@ -6937,4 +6683,4 @@ onnx = ["onnx", "onnxconverter-common", "onnxruntime_gpu", "onnxsim"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.11"
-content-hash = "d4b357468bfe398840abf8c9011767d00ddc950f14176894106e748a5fdcd649"
+content-hash = "9e825cd3ec4777fcaf2aac90adb3d68fbdb7b114f3bcae89de32ff0f49dc8956"
diff --git a/pyproject.toml b/pyproject.toml
index 8690288c..8241246a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "quadra"
-version = "2.1.13"
+version = "2.2.1"
 description = "Deep Learning experiment orchestration library"
 authors = [
 	"Federico Belotti <federico.belotti@orobix.com>",
@@ -40,12 +40,7 @@ quadra = "quadra.main:main"
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
 
-torch = [
-	{ url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp310-cp310-linux_x86_64.whl", markers = "sys_platform == 'linux' and python_version == '3.10'" },
-	{ url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp310-cp310-win_amd64.whl", markers = "sys_platform == 'win32' and python_version == '3.10'" },
-	{ url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp39-cp39-linux_x86_64.whl", markers = "sys_platform == 'linux' and python_version == '3.9'" },
-	{ url = "https://download.pytorch.org/whl/cu121/torch-2.1.2%2Bcu121-cp39-cp39-win_amd64.whl", markers = "sys_platform == 'win32' and python_version == '3.9'" },
-]
+torch = { version = "2.1.2", source = "torch_cu121" }
 torchvision = { version = "~0.16", source = "torch_cu121" }
 
 pytorch_lightning = "~2.1"
@@ -75,9 +70,9 @@ scikit_multilearn = "~0.2"
 tripy = "~1.0"
 h5py = "~3.8"
 timm = "0.9.12"
-# Right now only this ref supports timm 0.9.12
-segmentation_models_pytorch = { git = "https://github.com/qubvel/segmentation_models.pytorch", rev = "7b381f899ed472a477a89d381689caf535b5d0a6" }
-anomalib = { git = "https://github.com/orobix/anomalib.git", tag = "v0.7.0+obx.1.3.3" }
+
+segmentation_models_pytorch-orobix = "0.3.3.dev1"
+anomalib-orobix = "0.7.0.dev140"
 xxhash = "~3.2"
 torchinfo = "~1.8"
 typing_extensions = { version = "4.11.0", python = "<3.10" }
diff --git a/quadra/__init__.py b/quadra/__init__.py
index 02993008..c69109dd 100644
--- a/quadra/__init__.py
+++ b/quadra/__init__.py
@@ -1,4 +1,4 @@
-__version__ = "2.1.13"
+__version__ = "2.2.1"
 
 
 def get_version():