diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index fd05b524..6fbe9f1c 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -18,7 +18,6 @@ concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
   cancel-in-progress: true
 
-
 jobs:
   linting:
     name: Run linting/pre-commit checks
@@ -48,6 +47,7 @@ jobs:
           version: "latest"
           # https://github.com/astral-sh/setup-uv?tab=readme-ov-file#github-authentication-token
           github-token: ${{ secrets.GITHUB_TOKEN }}
+          python-version: "3.12"
       - name: Install dependencies
         run: uv sync --frozen --extra docs
       - name: Build the documentation (strict mode)
@@ -60,7 +60,7 @@ jobs:
       max-parallel: 4
       matrix:
         platform: [ubuntu-latest, macos-latest]
-        python-version: ["3.11"]
+        python-version: ["3.12"]
     steps:
       - uses: actions/checkout@v4
       - name: Install the latest version of uv
diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml
index dae23c20..e6c6c1d7 100644
--- a/.github/workflows/docs.yml
+++ b/.github/workflows/docs.yml
@@ -17,10 +17,7 @@ jobs:
           version: "latest"
           # https://github.com/astral-sh/setup-uv?tab=readme-ov-file#github-authentication-token
           github-token: ${{ secrets.GITHUB_TOKEN }}
-          cache-suffix: "3.10"
-
-      - name: Pin python-version
-        run: uv python pin 3.10
+          python-version: "3.12"
 
       - name: Install dependencies
         run: uv sync --extra docs --frozen
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index ce7577e6..acc4d281 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -3,7 +3,7 @@ default_language_version:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v5.0.0
+    rev: v6.0.0
     hooks:
       # list of supported hooks: https://pre-commit.com/hooks.html
       - id: trailing-whitespace
@@ -32,7 +32,7 @@ repos:
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: "v0.6.9"
+    rev: "v0.14.11"
     hooks:
       - id: ruff
         args: ["--line-length", "99", "--fix"]
@@ -41,7 +41,7 @@ repos:
   # python docstring formatting
   - repo: https://github.com/myint/docformatter
     # Don't autoupdate until https://github.com/PyCQA/docformatter/issues/293 is fixed
-    rev: eb1df347edd128b30cd3368dddc3aa65edcfac38
+    rev: v1.7.7
     hooks:
       - id: docformatter
         language: python
@@ -59,33 +59,34 @@ repos:
 
   # jupyter notebook cell output clearing
   - repo: https://github.com/kynan/nbstripout
-    rev: 0.7.1
+    rev: 0.8.2
     hooks:
       - id: nbstripout
         require_serial: true
 
   # md formatting
-  - repo: https://github.com/executablebooks/mdformat
-    rev: 0.7.17
-    hooks:
-      - id: mdformat
-        exclude: "docs/" # terrible, I know, but it's messing up everything with mkdocs fences!
-        args: ["--number"]
-        additional_dependencies:
-          - mdformat-gfm
-          - mdformat-tables
-          - mdformat_frontmatter
-          - mdformat-toc
-          - mdformat-config
-          - mdformat-black
-          # see https://github.com/KyleKing/mdformat-mkdocs
-          # Doesn't seem to work!
-          - mdformat-mkdocs[recommended]>=2.1.0
-        require_serial: true
+  # TODO: Getting errors with python 3.13. Turning off for now.
+  # - repo: https://github.com/executablebooks/mdformat
+  #   rev: 1.0.0
+  #   hooks:
+  #     - id: mdformat
+  #       exclude: "docs/" # terrible, I know, but it's messing up everything with mkdocs fences!
+  #       args: ["--number"]
+  #       additional_dependencies:
+  #         - mdformat-gfm
+  #         - mdformat-tables
+  #         - mdformat_frontmatter
+  #         - mdformat-toc
+  #         - mdformat-config
+  #         - mdformat-black
+  #         # see https://github.com/KyleKing/mdformat-mkdocs
+  #         # Doesn't seem to work!
+  #         - mdformat-mkdocs[recommended]>=2.1.0
+  #       require_serial: true
 
   # word spelling linter
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.3.0
+    rev: v2.4.1
     hooks:
       - id: codespell
         args:
diff --git a/.python-version b/.python-version
deleted file mode 100644
index 2c073331..00000000
--- a/.python-version
+++ /dev/null
@@ -1 +0,0 @@
-3.11
diff --git a/copier.yaml b/copier.yaml
index e52f29df..ba81acdd 100644
--- a/copier.yaml
+++ b/copier.yaml
@@ -65,11 +65,9 @@ python_version:
   question: "What Python version do you want to use?"
   required: true
   choices:
-    - "3.10"
-    - "3.11"
     - "3.12"
-    # - "3.13" # todo: There seem to be some dependency issues with python 3.13 that need fixing.
-  default: "3.10"
+    - "3.13" # todo: There seem to be some dependency issues with python 3.13 that need fixing.
+  default: "3.12"
 
 # IDEA: Simplify the repo creation part of the form for new users.
 # However, does that maybe make too many assumptions about how people will use this?
diff --git a/project/algorithms/callbacks/classification_metrics.py b/project/algorithms/callbacks/classification_metrics.py
index 54cf43b9..cfa14902 100644
--- a/project/algorithms/callbacks/classification_metrics.py
+++ b/project/algorithms/callbacks/classification_metrics.py
@@ -1,6 +1,6 @@
 import warnings
 from logging import getLogger as get_logger
-from typing import Literal, NotRequired, Required, TypedDict
+from typing import Literal, NotRequired, Required, TypedDict, override
 
 import lightning
 import torch
@@ -8,7 +8,6 @@
 from lightning import LightningModule, Trainer
 from torch import Tensor
 from torchmetrics.classification import MulticlassAccuracy
-from typing_extensions import override
 
 from project.utils.typing_utils.protocols import ClassificationDataModule
 
@@ -17,7 +16,7 @@
 
 class ClassificationOutputs(TypedDict, total=False):
     """The outputs that should be minimally returned from the training/val/test_step of
-    classification LightningModules so that metrics can be added aumatically by the
+    classification LightningModules so that metrics can be added automatically by the
     `ClassificationMetricsCallback`."""
 
     loss: NotRequired[torch.Tensor | float]
diff --git a/project/algorithms/callbacks/samples_per_second.py b/project/algorithms/callbacks/samples_per_second.py
index ecbd464f..ae06bb44 100644
--- a/project/algorithms/callbacks/samples_per_second.py
+++ b/project/algorithms/callbacks/samples_per_second.py
@@ -1,5 +1,5 @@
 import time
-from typing import Any, Generic, Literal
+from typing import Any, Literal, override
 
 import lightning
 import optree
@@ -8,18 +8,13 @@
 from lightning.pytorch.utilities.types import STEP_OUTPUT
 from torch import Tensor
 from torch.optim.optimizer import Optimizer
-from typing_extensions import TypeVar, override
 
 from project.utils.typing_utils import NestedMapping, is_sequence_of
 
-BatchType = TypeVar(
-    "BatchType",
-    bound=torch.Tensor | tuple[torch.Tensor, ...] | NestedMapping[str, torch.Tensor],
-    contravariant=True,
-)
+type _Batch = torch.Tensor | tuple[torch.Tensor, ...] | NestedMapping[str, torch.Tensor]
 
 
-class MeasureSamplesPerSecondCallback(lightning.Callback, Generic[BatchType]):
+class MeasureSamplesPerSecondCallback[BatchType: _Batch](lightning.Callback):
     def __init__(self, num_optimizers: int | None = None):
         super().__init__()
         self.last_step_times: dict[Literal["train", "val", "test"], float] = {}
diff --git a/project/algorithms/jax_ppo.py b/project/algorithms/jax_ppo.py
index da6bfc20..9082c9b6 100644
--- a/project/algorithms/jax_ppo.py
+++ b/project/algorithms/jax_ppo.py
@@ -13,7 +13,7 @@
 from collections.abc import Callable, Mapping, Sequence
 from logging import getLogger as get_logger
 from pathlib import Path
-from typing import Any, Generic, TypedDict
+from typing import Any, TypedDict
 
 import chex
 import flax.linen
@@ -77,7 +77,7 @@ class AdvantageMinibatch(flax.struct.PyTreeNode):
     targets: chex.Array
 
 
-class TrajectoryCollectionState(Generic[TEnvState], flax.struct.PyTreeNode):
+class TrajectoryCollectionState[TEnvState: gymnax.EnvState](flax.struct.PyTreeNode):
     """Struct containing the state related to the collection of data from the environment."""
 
     last_obs: jax.Array
@@ -88,7 +88,8 @@ class TrajectoryCollectionState(Generic[TEnvState], flax.struct.PyTreeNode):
     rng: chex.PRNGKey
 
 
-class PPOState(Generic[TEnvState], flax.struct.PyTreeNode):
+@flax.struct.dataclass
+class PPOState[TEnvState: gymnax.EnvState]:
     """Contains all the state of the `JaxRLExample` algorithm."""
 
     actor_ts: TrainState
@@ -97,10 +98,7 @@ class PPOState(Generic[TEnvState], flax.struct.PyTreeNode):
     data_collection_state: TrajectoryCollectionState[TEnvState]
 
 
-T = TypeVar("T")
-
-
-def field(
+def field[T](
     *,
     default: T | dataclasses._MISSING_TYPE = dataclasses.MISSING,
     default_factory: Callable[[], T] | dataclasses._MISSING_TYPE = dataclasses.MISSING,
@@ -207,10 +205,9 @@ def get_error_from_ppo_eval_metrics(metrics: EvalMetrics) -> tuple[str, float]:
     )
 
 
-class JaxRLExample(
+class JaxRLExample[TEnvState: gymnax.EnvState, TEnvParams: gymnax.EnvParams](
     flax.struct.PyTreeNode,
     JaxModule[PPOState[TEnvState], TrajectoryWithLastObs, EvalMetrics],
-    Generic[TEnvState, TEnvParams],
 ):
     """Example of an RL algorithm written in Jax: PPO, based on `rejax.PPO`.
 
diff --git a/project/algorithms/jax_ppo_test.py b/project/algorithms/jax_ppo_test.py
index 50569bd2..906a3f66 100644
--- a/project/algorithms/jax_ppo_test.py
+++ b/project/algorithms/jax_ppo_test.py
@@ -8,7 +8,7 @@
 from collections.abc import Callable, Iterable, Sequence
 from logging import getLogger
 from pathlib import Path
-from typing import Any
+from typing import Any, override
 
 import chex
 import gymnax
@@ -27,7 +27,6 @@
 from lightning.pytorch.utilities.types import STEP_OUTPUT
 from tensor_regression import TensorRegressionFixture
 from torch.utils.data import DataLoader
-from typing_extensions import override
 
 from project.algorithms.callbacks.samples_per_second import MeasureSamplesPerSecondCallback
 from project.main_test import experiment_commands_to_test
@@ -462,7 +461,7 @@ def debug_jit_warnings():
     # Temporarily make this particular warning into an error to help future-proof our jax code.
     import jax._src.deprecations
 
-    deprecations_to_trigger_error_for = ["tracer-hash"]
+    deprecations_to_trigger_error_for = []
     values_before = {}
     for dep in deprecations_to_trigger_error_for:
         if val := jax._src.deprecations._registered_deprecations.get(dep):
diff --git a/project/algorithms/lightning_module_tests.py b/project/algorithms/lightning_module_tests.py
index ff2188e5..a0f04a26 100644
--- a/project/algorithms/lightning_module_tests.py
+++ b/project/algorithms/lightning_module_tests.py
@@ -5,13 +5,13 @@
 
 from __future__ import annotations
 
+import abc
 import copy
 import dataclasses
-from abc import ABC
 from collections.abc import Mapping
 from logging import getLogger as get_logger
 from pathlib import Path
-from typing import Any, Generic, Literal, TypeVar, overload
+from typing import Any, Literal, overload
 
 import lightning
 import pytest
@@ -28,11 +28,9 @@
 
 logger = get_logger(__name__)
 
-LightningModuleType = TypeVar("LightningModuleType", bound=LightningModule)
-
 
 @pytest.mark.incremental  # https://docs.pytest.org/en/stable/example/simple.html#incremental-testing-test-steps
-class LightningModuleTests(Generic[LightningModuleType], ABC):
+class LightningModuleTests[LightningModuleType: LightningModule](abc.ABC):
     """Suite of generic tests for a LightningModule.
 
     Simply inherit from this class and decorate the class with the appropriate markers to get a set
diff --git a/project/algorithms/llm_finetuning.py b/project/algorithms/llm_finetuning.py
index bd1d6b0a..e5eef3d8 100644
--- a/project/algorithms/llm_finetuning.py
+++ b/project/algorithms/llm_finetuning.py
@@ -14,7 +14,7 @@
 from dataclasses import dataclass
 from logging import getLogger
 from pathlib import Path
-from typing import Concatenate, ParamSpec, TypeVar
+from typing import Concatenate
 
 import datasets
 import datasets.distributed
@@ -517,10 +517,7 @@ def get_hash_of(config_dataclass) -> str:
     return hashlib.md5(vals_string.encode()).hexdigest()
 
 
-V = TypeVar("V")
-
-
-def flatten_dict(d: NestedMapping[str, V]) -> dict[str, V]:
+def flatten_dict[V](d: NestedMapping[str, V]) -> dict[str, V]:
     result = {}
     for k, v in d.items():
         if isinstance(v, Mapping):
@@ -530,10 +527,7 @@ def flatten_dict(d: NestedMapping[str, V]) -> dict[str, V]:
     return result
 
 
-P = ParamSpec("P")
-
-
-def _try_to_load_prepared_dataset_from(
+def _try_to_load_prepared_dataset_from[**P](
     dataset_path: Path,
     _load_from_disk_fn: Callable[Concatenate[Path, P], Dataset | DatasetDict] = load_from_disk,
     *_load_from_disk_args: P.args,
diff --git a/project/algorithms/text_classifier_test.py b/project/algorithms/text_classifier_test.py
index 3f9cd490..2126b648 100644
--- a/project/algorithms/text_classifier_test.py
+++ b/project/algorithms/text_classifier_test.py
@@ -1,6 +1,6 @@
 from collections.abc import Mapping
 from pathlib import Path
-from typing import Any
+from typing import Any, override
 
 import lightning
 import pytest
@@ -9,7 +9,6 @@
 from tensor_regression import TensorRegressionFixture
 from torch import Tensor
 from transformers import PreTrainedModel
-from typing_extensions import override
 
 from project.algorithms.text_classifier import TextClassifier
 from project.datamodules.text.text_classification import TextClassificationDataModule
diff --git a/project/conftest.py b/project/conftest.py
index 69dfbd0b..d57f5ff3 100644
--- a/project/conftest.py
+++ b/project/conftest.py
@@ -70,7 +70,7 @@
 from contextlib import contextmanager
 from logging import getLogger as get_logger
 from pathlib import Path
-from typing import Any, Literal, TypeVar
+from typing import Any, Literal
 
 import hydra.errors
 import lightning
@@ -554,9 +554,7 @@ def _longest_common_prefix(strings: list[str]):
                     return shortest[:i]
         return shortest
 
-    T = TypeVar("T")
-
-    def _assert_type(v: Any, t: type[T]) -> T:
+    def _assert_type[T](v: Any, t: type[T]) -> T:
         assert isinstance(v, t)
         return v
 
diff --git a/project/datamodules/datamodule_tests.py b/project/datamodules/datamodule_tests.py
index f03a017f..4af7df42 100644
--- a/project/datamodules/datamodule_tests.py
+++ b/project/datamodules/datamodule_tests.py
@@ -1,11 +1,9 @@
 import abc
 import sys
-from typing import Generic, TypeVar
 
 import hydra_zen
 import omegaconf
 import pytest
-from lightning import LightningDataModule
 from lightning.fabric.utilities.exceptions import MisconfigurationException
 from lightning.pytorch.trainer.states import RunningStage
 from tensor_regression.fixture import TensorRegressionFixture
@@ -14,19 +12,23 @@
 from project.algorithms.lightning_module_tests import convert_list_and_tuples_to_dicts
 from project.conftest import algorithm_config
 from project.utils.testutils import IN_GITHUB_CLOUD_CI
-
-DataModuleType = TypeVar("DataModuleType", bound=LightningDataModule)
+from project.utils.typing_utils.protocols import DataModule
 
 # Use a dummy, empty algorithm, to keep the datamodule tests independent of the algorithms.
 # This is a unit test for the datamodule, so we don't want to involve the algorithm here.
 
 
+# NOTE: Here these parametrizations are actually inherited by all the test classes that inherit from DataModuleTests
+# and run tests for different datamodules. This is a bit unusual, but avoids us having to repeat these parametrizations
+# in every single datamodule test class.
+
+
 @pytest.mark.skipif(
     IN_GITHUB_CLOUD_CI and sys.platform == "darwin",
     reason="Getting weird bugs with MacOS on GitHub CI.",
 )
 @pytest.mark.parametrize(algorithm_config.__name__, ["no_op"], indirect=True, ids=[""])
-class DataModuleTests(Generic[DataModuleType], abc.ABC):
+class DataModuleTests[DataModuleType: DataModule](abc.ABC):
     @pytest.fixture(
         scope="class",
         params=[
diff --git a/project/datamodules/image_classification/image_classification_test.py b/project/datamodules/image_classification/image_classification_test.py
index 782d32b6..0f0b4e30 100644
--- a/project/datamodules/image_classification/image_classification_test.py
+++ b/project/datamodules/image_classification/image_classification_test.py
@@ -1,5 +1,4 @@
 from pathlib import Path
-from typing import TypeVar
 
 import pytest
 from lightning.pytorch.trainer.states import RunningStage
@@ -12,12 +11,10 @@
 )
 from project.datamodules.vision_test import VisionDataModuleTests
 
-ImageClassificationDataModuleType = TypeVar(
-    "ImageClassificationDataModuleType", bound=ImageClassificationDataModule
-)
-
 
-class ImageClassificationDataModuleTests(VisionDataModuleTests[ImageClassificationDataModuleType]):
+class ImageClassificationDataModuleTests[
+    ImageClassificationDataModuleType: ImageClassificationDataModule
+](VisionDataModuleTests[ImageClassificationDataModuleType]):
     """Tests for a datamodule/dataset for image classification.
 
     This is a simple data regression test for now.
diff --git a/project/datamodules/text/text_classification.py b/project/datamodules/text/text_classification.py
index ffbb9aa8..c0a4e623 100644
--- a/project/datamodules/text/text_classification.py
+++ b/project/datamodules/text/text_classification.py
@@ -241,7 +241,8 @@ def convert_to_features(self, example_batch, indices=None):
         features = self.tokenizer.batch_encode_plus(
             texts_or_text_pairs,
             max_length=self.max_seq_length,
-            pad_to_max_length=True,
+            # pad_to_max_length=True,
+            padding="max_length",
             truncation=True,
         )
         if "label" in example_batch and "labels" not in example_batch:
diff --git a/project/datamodules/vision.py b/project/datamodules/vision.py
index 140b4f06..9bb81f11 100644
--- a/project/datamodules/vision.py
+++ b/project/datamodules/vision.py
@@ -5,7 +5,7 @@
 from collections.abc import Callable
 from logging import getLogger as get_logger
 from pathlib import Path
-from typing import ClassVar, Concatenate, Literal, ParamSpec, TypeVar
+from typing import ClassVar, Concatenate, Literal
 
 import torch
 import torchvision.transforms
@@ -22,11 +22,8 @@
 
 logger = get_logger(__name__)
 
-BatchType_co = TypeVar("BatchType_co", covariant=True)
-P = ParamSpec("P")
 
-
-class VisionDataModule(LightningDataModule, DataModule[BatchType_co]):
+class VisionDataModule[BatchType_co](LightningDataModule, DataModule[BatchType_co]):
     """A LightningDataModule for image datasets.
 
     (Taken from pl_bolts which is not very well maintained.)
@@ -220,7 +217,7 @@ def _get_splits(self, len_dataset: int) -> list[int]:
     def default_transforms(self) -> Callable:
         """Default transform for the dataset."""
 
-    def train_dataloader(
+    def train_dataloader[**P](
         self,
         _dataloader_fn: Callable[Concatenate[Dataset, P], DataLoader] = DataLoader,
         *args: P.args,
@@ -238,7 +235,7 @@ def train_dataloader(
             **kwargs,
         )
 
-    def val_dataloader(
+    def val_dataloader[**P](
         self,
         _dataloader_fn: Callable[Concatenate[Dataset, P], DataLoader] = DataLoader,
         *args: P.args,
@@ -255,7 +252,7 @@ def val_dataloader(
             **kwargs,
         )
 
-    def test_dataloader(
+    def test_dataloader[**P](
         self,
         _dataloader_fn: Callable[Concatenate[Dataset, P], DataLoader] = DataLoader,
         *args: P.args,
@@ -272,7 +269,7 @@ def test_dataloader(
             **kwargs,
         )
 
-    def _data_loader(
+    def _data_loader[**P](
         self,
         dataset: Dataset,
         _dataloader_fn: Callable[Concatenate[Dataset, P], DataLoader] = DataLoader,
@@ -335,5 +332,5 @@ def _contains_normalization_transform(transforms: Callable) -> bool:
     if isinstance(transforms, torchvision.transforms.Compose | torchvision.transforms.v2.Compose):
         return any(_contains_normalization_transform(t) for t in transforms.transforms)
     if isinstance(transforms, torch.nn.Sequential):
-        return any(_contains_normalization_transform(t) for t in transforms.transforms)
+        return any(_contains_normalization_transform(t) for t in transforms)
     return False
diff --git a/project/datamodules/vision_test.py b/project/datamodules/vision_test.py
index 776e3a58..02263652 100644
--- a/project/datamodules/vision_test.py
+++ b/project/datamodules/vision_test.py
@@ -1,7 +1,6 @@
 import sys
 from logging import getLogger
 from pathlib import Path
-from typing import TypeVar
 
 import matplotlib.pyplot as plt
 import pytest
@@ -14,10 +13,11 @@
 from project.datamodules.vision import VisionDataModule
 
 logger = getLogger(__name__)
-VisionDataModuleType = TypeVar("VisionDataModuleType", bound=VisionDataModule)
 
 
-class VisionDataModuleTests(DataModuleTests[VisionDataModuleType]):
+class VisionDataModuleTests[VisionDataModuleType: VisionDataModule](
+    DataModuleTests[VisionDataModuleType]
+):
     """Tests for a datamodule/dataset for vision tasks.
 
     This is a simple data regression test for now.
diff --git a/project/utils/hydra_utils.py b/project/utils/hydra_utils.py
index 9c141db2..dea0184d 100644
--- a/project/utils/hydra_utils.py
+++ b/project/utils/hydra_utils.py
@@ -12,7 +12,6 @@
 from logging import getLogger as get_logger
 from typing import (
     Any,
-    TypeVar,
 )
 
 import hydra.utils
@@ -254,8 +253,7 @@ def instance_attr(
                 instantiated_obj = instantiate(obj)
             except Exception as err:
                 logger.error(
-                    f"Unable to instantiate {obj} to get the missing {attr_part} "
-                    f"attribute: {err}"
+                    f"Unable to instantiate {obj} to get the missing {attr_part} attribute: {err}"
                 )
                 break
             new_instantiated_objects[path_so_far] = instantiated_obj
@@ -347,10 +345,7 @@ def _being_called_by(*functions: Callable) -> bool:
     return False
 
 
-Target = TypeVar("Target")
-
-
-def make_config_and_store(
+def make_config_and_store[Target](
     target: Callable[..., Target], *, store: hydra_zen.ZenStore, **overrides
 ):
     """Creates a config dataclass for the given target and stores it in the config store.
diff --git a/project/utils/typing_utils/__init__.py b/project/utils/typing_utils/__init__.py
index e107ca81..b4f83720 100644
--- a/project/utils/typing_utils/__init__.py
+++ b/project/utils/typing_utils/__init__.py
@@ -2,11 +2,10 @@
 
 from __future__ import annotations
 
-from collections.abc import Iterable, Mapping, Sequence
+from collections.abc import Mapping, Sequence
 from typing import Any, NewType, TypeGuard
 
 from hydra_zen.typing import Builds
-from typing_extensions import TypeVar
 
 from .protocols import DataModule
 
@@ -15,20 +14,14 @@
 H = NewType("H", int)
 W = NewType("W", int)
 
-
-T = TypeVar("T")
-K = TypeVar("K")
-V = TypeVar("V")
-
-HydraConfigFor = Builds[type[T]]
+type HydraConfigFor[T] = Builds[type[T]]
 """Type annotation to say "a hydra config that returns an object of type T when instantiated"."""
 
 
-NestedMapping = Mapping[K, V | "NestedMapping[K, V]"]
-PyTree = T | Iterable["PyTree[T]"] | Mapping[Any, "PyTree[T]"]
+type NestedMapping[K, V] = Mapping[K, V | NestedMapping[K, V]]
 
 
-def is_sequence_of(
+def is_sequence_of[V](
     object: Any, item_type: type[V] | tuple[type[V], ...]
 ) -> TypeGuard[Sequence[V]]:
     """Used to check (and tell the type checker) that `object` is a sequence of items of this
@@ -36,7 +29,9 @@ def is_sequence_of(
     return isinstance(object, Sequence) and all(isinstance(value, item_type) for value in object)
 
 
-def is_mapping_of(object: Any, key_type: type[K], value_type: type[V]) -> TypeGuard[Mapping[K, V]]:
+def is_mapping_of[K, V](
+    object: Any, key_type: type[K], value_type: type[V]
+) -> TypeGuard[Mapping[K, V]]:
     """Used to check (and tell the type checker) that `object` is a mapping with keys and values of
     the given types."""
     return isinstance(object, Mapping) and all(
diff --git a/project/utils/typing_utils/protocols.py b/project/utils/typing_utils/protocols.py
index 28d28b01..1d1296f4 100644
--- a/project/utils/typing_utils/protocols.py
+++ b/project/utils/typing_utils/protocols.py
@@ -1,18 +1,15 @@
 from __future__ import annotations
 
 import typing
-from typing import Literal, ParamSpec, Protocol, TypeVar, runtime_checkable
+from typing import Literal, Protocol, runtime_checkable
 
 if typing.TYPE_CHECKING:
     from torch import nn
     from torch.utils.data import DataLoader
 
-P = ParamSpec("P")
-OutT = TypeVar("OutT", covariant=True)
-
 
 @runtime_checkable
-class Module(Protocol[P, OutT]):
+class Module[**P, OutT](Protocol):
     """Small protocol that can be used to annotate the input/output types of `torch.nn.Module`s."""
 
     def forward(self, *args: P.args, **kwargs: P.kwargs) -> OutT:
@@ -35,11 +32,8 @@ def __call__(self, *args: P.args, **kwagrs: P.kwargs) -> OutT: ...
         to = nn.Module().to
 
 
-BatchType = TypeVar("BatchType", covariant=True)
-
-
 @runtime_checkable
-class DataModule(Protocol[BatchType]):
+class DataModule[BatchType](Protocol):
     """Protocol that shows the minimal attributes / methods of the `LightningDataModule` class.
 
     This is used to type hint the batches that are yielded by the DataLoaders.
@@ -53,7 +47,7 @@ def train_dataloader(self) -> DataLoader[BatchType]: ...
 
 
 @runtime_checkable
-class ClassificationDataModule(DataModule[BatchType], Protocol):
-    """Protocol that matches "datamodules with a 'num_classes' int attribute."""
+class ClassificationDataModule[BatchType](DataModule[BatchType], Protocol):
+    """Protocol for classification datamodules (datasets) with a 'num_classes' int attribute."""
 
     num_classes: int
diff --git a/pyproject.toml b/pyproject.toml
index 83360639..a841f371 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,7 +15,7 @@ dependencies = [
     "torchvision>=0.19.0",
     "rich>=13.7.1",
     "tqdm>=4.66.5",
-    "hydra-zen==0.13.1rc1",
+    "hydra-zen>=0.16.0",
     "matplotlib>=3.9.2",
     "optree>=0.15.0",                 # to get tree ops without needing jax as a dependency.
     # Hugging Face dependencies:
@@ -34,10 +34,11 @@ dependencies = [
     "hydra-colorlog>=1.2.0",
     "remote-slurm-executor",
     "hydra-auto-schema>=0.0.7",
+    "orion>=0.2.8",
     "hydra-orion-sweeper>=1.6.4",
 ]
 readme = "README.md"
-requires-python = ">= 3.11,<3.14"
+requires-python = ">= 3.12,<3.14"
 
 [dependency-groups]
 dev = [
@@ -133,3 +134,6 @@ torch = [
 torchvision = [
     { index = "pytorch-cu130", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
 ]
+
+# note: Orion doesn't yet (2026-01-13) have a released build for python 3.12+ on PyPI.
+orion = { git = "https://github.com/Epistimio/orion", tag = "v0.2.8" }
diff --git a/pyproject.toml.jinja b/pyproject.toml.jinja
index e190c142..1eb22b0e 100644
--- a/pyproject.toml.jinja
+++ b/pyproject.toml.jinja
@@ -15,7 +15,7 @@ dependencies = [
     "torchvision>=0.19.0",
     "rich>=13.7.1",
     "tqdm>=4.66.5",
-    "hydra-zen==0.13.1rc1",
+    "hydra-zen>=0.16.0",
     "matplotlib>=3.9.2",
     "optree>=0.15.0",                 # to get tree ops without needing jax as a dependency.
     # Hugging Face dependencies:
@@ -34,6 +34,7 @@ dependencies = [
     "hydra-colorlog>=1.2.0",
     "remote-slurm-executor",
     "hydra-auto-schema>=0.0.7",
+    "orion>=0.2.8",
     "hydra-orion-sweeper>=1.6.4",
 ]
 readme = "README.md"
@@ -109,3 +110,4 @@ torch = [
 torchvision = [
     { index = "pytorch-cu130", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
 ]
+orion = { git = "https://github.com/Epistimio/orion", tag = "v0.2.8" }
diff --git a/tests/test_template.py b/tests/test_template.py
index f8ec384d..fe759c4d 100644
--- a/tests/test_template.py
+++ b/tests/test_template.py
@@ -13,7 +13,6 @@
 import tomli
 import yaml
 from copier import Worker
-from copier.vcs import get_git
 from plumbum import local
 
 import project
@@ -23,6 +22,23 @@
 
 logger = getLogger(__name__)
 
+
+def get_git(context_dir: str | Path | None = None):
+    """Gets `git` command, or fails if it's not available."""
+
+    GIT_USER_NAME = "Copier"
+    GIT_USER_EMAIL = "copier@copier"
+    command = local["git"].with_env(
+        GIT_AUTHOR_NAME=GIT_USER_NAME,
+        GIT_AUTHOR_EMAIL=GIT_USER_EMAIL,
+        GIT_COMMITTER_NAME=GIT_USER_NAME,
+        GIT_COMMITTER_EMAIL=GIT_USER_EMAIL,
+    )
+    if context_dir:
+        command = command["-C", context_dir]
+    return command
+
+
 example_folder = Path(project.algorithms.__file__).parent
 examples: list[str] = [
     p.relative_to(example_folder).stem
@@ -35,7 +51,7 @@
     )
 ]
 
-_DEFAULT_PYTHON_VERSION = "3.11"
+_DEFAULT_PYTHON_VERSION = "3.12"
 """The default choice of python version in the copier.yaml file."""
 
 _project_fixture_scope = "module"
@@ -213,18 +229,9 @@ def project_from_template(
         # These can be very slow but are super important!
         # don't run these unless --slow argument is passed to pytest, to save some time.
         # "3.10",
-        "3.11",
-        pytest.param("3.12", marks=pytest.mark.slow),
-        pytest.param(
-            "3.13",
-            marks=[
-                pytest.mark.slow,
-                pytest.mark.xfail(
-                    reason="TODO: Update dependencies (torch, jax, t-j-i, mujoco, ...) for python 3.13",
-                    strict=True,
-                ),
-            ],
-        ),
+        # "3.11",
+        "3.12",
+        "3.13",
     ],
     indirect=True,
 )
@@ -408,7 +415,7 @@ def test_update_project(
 
     with modification(project_root, copier_answers, template_version_used):
         # Need to commit changes for copier to accept to update.
-        git = get_git().with_cwd(project_root)
+        git = get_git(context_dir=project_root)
         # TODO: Double-check that these changes only affect the temporary cloned repo, not this
         # current dev repo.
         git("config", "commit.gpgsign", "false")
diff --git a/uv.lock b/uv.lock
index dc15f926..c93882a9 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,19 +1,15 @@
 version = 1
 revision = 3
-requires-python = ">=3.11, <3.14"
+requires-python = ">=3.12, <3.14"
 resolution-markers = [
     "(python_full_version >= '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.13' and platform_python_implementation != 'CPython' and sys_platform == 'linux')",
-    "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'",
     "python_full_version >= '3.13' and sys_platform == 'win32'",
+    "python_full_version >= '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'",
+    "(python_full_version < '3.13' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.13' and platform_python_implementation != 'CPython' and sys_platform == 'linux')",
+    "python_full_version < '3.13' and sys_platform == 'win32'",
+    "python_full_version < '3.13' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'",
     "python_full_version >= '3.13' and sys_platform != 'linux' and sys_platform != 'win32'",
-    "(python_full_version == '3.12.*' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version == '3.12.*' and platform_python_implementation != 'CPython' and sys_platform == 'linux')",
-    "python_full_version == '3.12.*' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'",
-    "(python_full_version < '3.12' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.12' and platform_python_implementation != 'CPython' and sys_platform == 'linux')",
-    "python_full_version < '3.12' and platform_machine == 'aarch64' and platform_python_implementation == 'CPython' and sys_platform == 'linux'",
-    "python_full_version == '3.12.*' and sys_platform == 'win32'",
-    "python_full_version == '3.12.*' and sys_platform != 'linux' and sys_platform != 'win32'",
-    "python_full_version < '3.12' and sys_platform == 'win32'",
-    "python_full_version < '3.12' and sys_platform != 'linux' and sys_platform != 'win32'",
+    "python_full_version < '3.13' and sys_platform != 'linux' and sys_platform != 'win32'",
 ]
 
 [[package]]
@@ -58,23 +54,6 @@ dependencies = [
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