diff --git a/poetry.lock b/poetry.lock
index 772545e..1ccaabe 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -59,13 +59,13 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "click"
-version = "8.1.7"
+version = "8.1.8"
 description = "Composable command line interface toolkit"
 optional = false
 python-versions = ">=3.7"
 files = [
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-    {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"},
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+    {file = "click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a"},
 ]
 
 [package.dependencies]
@@ -104,73 +104,73 @@ lz4 = ["lz4"]
 
 [[package]]
 name = "coverage"
-version = "7.6.7"
+version = "7.6.9"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.9"
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 [package.extras]
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 [[package]]
@@ -540,22 +557,19 @@ testing = ["pytest", "pytest-benchmark"]
 
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-version = "2.9.2"
+version = "2.10.4"
 description = "Data validation using Python type hints"
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-    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
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+typing-extensions = ">=4.12.2"
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
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@@ -664,13 +689,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pyright"
-version = "1.1.389"
+version = "1.1.391"
 description = "Command line wrapper for pyright"
 optional = false
 python-versions = ">=3.7"
 files = [
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@@ -774,29 +804,29 @@ files = [
 
 [[package]]
 name = "ruff"
-version = "0.7.4"
+version = "0.8.4"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 files = [
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 [[package]]
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+version = "2.2.1"
 description = "A lil' TOML parser"
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 python-versions = ">=3.8"
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+    {file = "tomli-2.2.1-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:40741994320b232529c802f8bc86da4e1aa9f413db394617b9a256ae0f9a7f77"},
+    {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:400e720fe168c0f8521520190686ef8ef033fb19fc493da09779e592861b78c6"},
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+    {file = "tomli-2.2.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:b82ebccc8c8a36f2094e969560a1b836758481f3dc360ce9a3277c65f374285e"},
+    {file = "tomli-2.2.1-cp312-cp312-win32.whl", hash = "sha256:889f80ef92701b9dbb224e49ec87c645ce5df3fa2cc548664eb8a25e03127a98"},
+    {file = "tomli-2.2.1-cp312-cp312-win_amd64.whl", hash = "sha256:7fc04e92e1d624a4a63c76474610238576942d6b8950a2d7f908a340494e67e4"},
+    {file = "tomli-2.2.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f4039b9cbc3048b2416cc57ab3bda989a6fcf9b36cf8937f01a6e731b64f80d7"},
+    {file = "tomli-2.2.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:286f0ca2ffeeb5b9bd4fcc8d6c330534323ec51b2f52da063b11c502da16f30c"},
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+    {file = "tomli-2.2.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a198f10c4d1b1375d7687bc25294306e551bf1abfa4eace6650070a5c1ae2744"},
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+    {file = "tomli-2.2.1-cp313-cp313-win_amd64.whl", hash = "sha256:a38aa0308e754b0e3c67e344754dff64999ff9b513e691d0e786265c93583c69"},
+    {file = "tomli-2.2.1-py3-none-any.whl", hash = "sha256:cb55c73c5f4408779d0cf3eef9f762b9c9f147a77de7b258bef0a5628adc85cc"},
+    {file = "tomli-2.2.1.tar.gz", hash = "sha256:cd45e1dc79c835ce60f7404ec8119f2eb06d38b1deba146f07ced3bbc44505ff"},
 ]
 
 [[package]]
@@ -835,4 +895,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.14"
-content-hash = "225a12c74e0d396a4410b06afafda668ada5fd17766f9957760b748777659330"
+content-hash = "1d9c49d01d3718031018269d63c26ff2034905573e363c24a135bacb06b5f390"
diff --git a/pydantic_numpy/__init__.py b/pydantic_numpy/__init__.py
index bac44f7..a5b3afb 100644
--- a/pydantic_numpy/__init__.py
+++ b/pydantic_numpy/__init__.py
@@ -1,4 +1,3 @@
 from pydantic_numpy.helper.annotation import np_array_pydantic_annotated_typing
-from pydantic_numpy.typing.n_dimensional import *
 
 __all__ = ["np_array_pydantic_annotated_typing", "model", "typing"]
diff --git a/pydantic_numpy/helper/annotation.py b/pydantic_numpy/helper/annotation.py
index d0488c1..1cc8fe9 100644
--- a/pydantic_numpy/helper/annotation.py
+++ b/pydantic_numpy/helper/annotation.py
@@ -1,6 +1,6 @@
 from collections.abc import Sequence
 from pathlib import Path
-from typing import Any, Callable, ClassVar, Iterable, Optional, Union
+from typing import Any, Callable, ClassVar, Iterable, Optional, Union, cast
 
 import numpy as np
 import numpy.typing as npt
@@ -55,12 +55,12 @@ def pd_np_native_numpy_array_to_data_dict_serializer(array_like: npt.ArrayLike)
     """
     array = np.array(array_like)
 
-    if issubclass(array.dtype.type, np.timedelta64) or issubclass(array.dtype.type, np.datetime64):
-        data = array.astype(int).tolist()
-    else:
-        data = array.astype(float).tolist()
+    data = array.astype(
+        int if issubclass(array.dtype.type, np.timedelta64) or issubclass(array.dtype.type, np.datetime64) else float
+    ).tolist()
+    cast_data = cast(list, data)
 
-    return NumpyArrayTypeData(data_type=str(array.dtype), data=data)
+    return NumpyArrayTypeData(data_type=str(array.dtype), data=cast_data)
 
 
 def pd_np_native_numpy_array_json_schema_from_type_data(
diff --git a/pydantic_numpy/typing/__init__.py b/pydantic_numpy/typing/__init__.py
index 19d9d34..0e7b88c 100644
--- a/pydantic_numpy/typing/__init__.py
+++ b/pydantic_numpy/typing/__init__.py
@@ -1,8 +1,4 @@
-from pydantic_numpy.typing.i_dimensional import *
-from pydantic_numpy.typing.ii_dimensional import *
-from pydantic_numpy.typing.iii_dimensional import *
-from pydantic_numpy.typing.n_dimensional import *
-from pydantic_numpy.typing.strict_data_type.i_dimensional import *
-from pydantic_numpy.typing.strict_data_type.ii_dimensional import *
-from pydantic_numpy.typing.strict_data_type.iii_dimensional import *
-from pydantic_numpy.typing.strict_data_type.n_dimensional import *
+from pydantic_numpy.typing.type_safe.i_dimensional import *
+from pydantic_numpy.typing.type_safe.ii_dimensional import *
+from pydantic_numpy.typing.type_safe.iii_dimensional import *
+from pydantic_numpy.typing.type_safe.n_dimensional import *
diff --git a/pydantic_numpy/typing/strict_data_type/__init__.py b/pydantic_numpy/typing/type_safe/__init__.py
similarity index 100%
rename from pydantic_numpy/typing/strict_data_type/__init__.py
rename to pydantic_numpy/typing/type_safe/__init__.py
diff --git a/pydantic_numpy/typing/strict_data_type/i_dimensional.py b/pydantic_numpy/typing/type_safe/i_dimensional.py
similarity index 67%
rename from pydantic_numpy/typing/strict_data_type/i_dimensional.py
rename to pydantic_numpy/typing/type_safe/i_dimensional.py
index 056f6f2..503ad67 100644
--- a/pydantic_numpy/typing/strict_data_type/i_dimensional.py
+++ b/pydantic_numpy/typing/type_safe/i_dimensional.py
@@ -1,116 +1,122 @@
-from typing import Annotated
+from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
-NpStrict1DArrayInt64 = Annotated[
+Np1DArray: TypeAlias = Annotated[
+    np.ndarray[tuple[int], np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(data_type=None, dimensions=1, strict_data_typing=False),
+]
+
+Np1DArrayInt64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int64]],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayInt32 = Annotated[
+Np1DArrayInt32: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int32]],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayInt16 = Annotated[
+Np1DArrayInt16: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int16]],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayInt8 = Annotated[
+Np1DArrayInt8: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int8]],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint64 = Annotated[
+Np1DArrayUint64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint64]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint32 = Annotated[
+Np1DArrayUint32: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint32]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint16 = Annotated[
+Np1DArrayUint16: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint16]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint8 = Annotated[
+Np1DArrayUint8: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint8]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFpLongDouble = Annotated[
+Np1DArrayFpLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.longdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFp64 = Annotated[
+Np1DArrayFp64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.float64]],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFp32 = Annotated[
+Np1DArrayFp32: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.float32]],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFp16 = Annotated[
+Np1DArrayFp16: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.float16]],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayComplexLongDouble = Annotated[
+Np1DArrayComplexLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.clongdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayComplex128 = Annotated[
+Np1DArrayComplex128: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.complex128]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayComplex64 = Annotated[
+Np1DArrayComplex64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.complex64]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayBool = Annotated[
+Np1DArrayBool: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.bool_]],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayDatetime64 = Annotated[
+Np1DArrayDatetime64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.datetime64]],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayTimedelta64 = Annotated[
+Np1DArrayTimedelta64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.timedelta64]],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=1, strict_data_typing=True),
 ]
 
 __all__ = [
-    "NpStrict1DArrayInt64",
-    "NpStrict1DArrayInt32",
-    "NpStrict1DArrayInt16",
-    "NpStrict1DArrayInt8",
-    "NpStrict1DArrayUint64",
-    "NpStrict1DArrayUint32",
-    "NpStrict1DArrayUint16",
-    "NpStrict1DArrayUint8",
-    "NpStrict1DArrayFpLongDouble",
-    "NpStrict1DArrayFp64",
-    "NpStrict1DArrayFp32",
-    "NpStrict1DArrayFp16",
-    "NpStrict1DArrayComplexLongDouble",
-    "NpStrict1DArrayComplex128",
-    "NpStrict1DArrayComplex64",
-    "NpStrict1DArrayBool",
-    "NpStrict1DArrayDatetime64",
-    "NpStrict1DArrayTimedelta64",
+    "Np1DArray",
+    "Np1DArrayInt64",
+    "Np1DArrayInt32",
+    "Np1DArrayInt16",
+    "Np1DArrayInt8",
+    "Np1DArrayUint64",
+    "Np1DArrayUint32",
+    "Np1DArrayUint16",
+    "Np1DArrayUint8",
+    "Np1DArrayFpLongDouble",
+    "Np1DArrayFp64",
+    "Np1DArrayFp32",
+    "Np1DArrayFp16",
+    "Np1DArrayComplexLongDouble",
+    "Np1DArrayComplex128",
+    "Np1DArrayComplex64",
+    "Np1DArrayBool",
+    "Np1DArrayDatetime64",
+    "Np1DArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/strict_data_type/ii_dimensional.py b/pydantic_numpy/typing/type_safe/ii_dimensional.py
similarity index 67%
rename from pydantic_numpy/typing/strict_data_type/ii_dimensional.py
rename to pydantic_numpy/typing/type_safe/ii_dimensional.py
index 6f07236..068e7d0 100644
--- a/pydantic_numpy/typing/strict_data_type/ii_dimensional.py
+++ b/pydantic_numpy/typing/type_safe/ii_dimensional.py
@@ -1,116 +1,122 @@
-from typing import Annotated
+from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
-NpStrict2DArrayInt64 = Annotated[
+Np2DArray: TypeAlias = Annotated[
+    np.ndarray[tuple[int, int], np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(data_type=None, dimensions=2, strict_data_typing=False),
+]
+
+Np2DArrayInt64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int64]],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayInt32 = Annotated[
+Np2DArrayInt32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int32]],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayInt16 = Annotated[
+Np2DArrayInt16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int16]],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayInt8 = Annotated[
+Np2DArrayInt8: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int8]],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint64 = Annotated[
+Np2DArrayUint64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint64]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint32 = Annotated[
+Np2DArrayUint32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint32]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint16 = Annotated[
+Np2DArrayUint16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint16]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint8 = Annotated[
+Np2DArrayUint8: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint8]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFpLongDouble = Annotated[
+Np2DArrayFpLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.longdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFp64 = Annotated[
+Np2DArrayFp64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.float64]],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFp32 = Annotated[
+Np2DArrayFp32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.float32]],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFp16 = Annotated[
+Np2DArrayFp16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.float16]],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayComplexLongDouble = Annotated[
+Np2DArrayComplexLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.clongdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayComplex128 = Annotated[
+Np2DArrayComplex128: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.complex128]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayComplex64 = Annotated[
+Np2DArrayComplex64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.complex64]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayBool = Annotated[
+Np2DArrayBool: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.bool_]],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayDatetime64 = Annotated[
+Np2DArrayDatetime64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.datetime64]],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayTimedelta64 = Annotated[
+Np2DArrayTimedelta64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.timedelta64]],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=2, strict_data_typing=True),
 ]
 
 __all__ = [
-    "NpStrict2DArrayInt64",
-    "NpStrict2DArrayInt32",
-    "NpStrict2DArrayInt16",
-    "NpStrict2DArrayInt8",
-    "NpStrict2DArrayUint64",
-    "NpStrict2DArrayUint32",
-    "NpStrict2DArrayUint16",
-    "NpStrict2DArrayUint8",
-    "NpStrict2DArrayFpLongDouble",
-    "NpStrict2DArrayFp64",
-    "NpStrict2DArrayFp32",
-    "NpStrict2DArrayFp16",
-    "NpStrict2DArrayComplexLongDouble",
-    "NpStrict2DArrayComplex128",
-    "NpStrict2DArrayComplex64",
-    "NpStrict2DArrayBool",
-    "NpStrict2DArrayDatetime64",
-    "NpStrict2DArrayTimedelta64",
+    "Np2DArray",
+    "Np2DArrayInt64",
+    "Np2DArrayInt32",
+    "Np2DArrayInt16",
+    "Np2DArrayInt8",
+    "Np2DArrayUint64",
+    "Np2DArrayUint32",
+    "Np2DArrayUint16",
+    "Np2DArrayUint8",
+    "Np2DArrayFpLongDouble",
+    "Np2DArrayFp64",
+    "Np2DArrayFp32",
+    "Np2DArrayFp16",
+    "Np2DArrayComplexLongDouble",
+    "Np2DArrayComplex128",
+    "Np2DArrayComplex64",
+    "Np2DArrayBool",
+    "Np2DArrayDatetime64",
+    "Np2DArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/strict_data_type/iii_dimensional.py b/pydantic_numpy/typing/type_safe/iii_dimensional.py
similarity index 68%
rename from pydantic_numpy/typing/strict_data_type/iii_dimensional.py
rename to pydantic_numpy/typing/type_safe/iii_dimensional.py
index 89314bc..b6b83f8 100644
--- a/pydantic_numpy/typing/strict_data_type/iii_dimensional.py
+++ b/pydantic_numpy/typing/type_safe/iii_dimensional.py
@@ -1,116 +1,122 @@
-from typing import Annotated
+from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
-NpStrict3DArrayInt64 = Annotated[
+Np3DArray: TypeAlias = Annotated[
+    np.ndarray[tuple[int, int, int], np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(data_type=None, dimensions=3, strict_data_typing=False),
+]
+
+Np3DArrayInt64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.int64]],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayInt32 = Annotated[
+Np3DArrayInt32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.int32]],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayInt16 = Annotated[
+Np3DArrayInt16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.int16]],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayInt8 = Annotated[
+Np3DArrayInt8: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.int8]],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayUint64 = Annotated[
+Np3DArrayUint64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.uint64]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayUint32 = Annotated[
+Np3DArrayUint32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.uint32]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayUint16 = Annotated[
+Np3DArrayUint16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.uint16]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayUint8 = Annotated[
+Np3DArrayUint8: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.uint8]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayFpLongDouble = Annotated[
+Np3DArrayFpLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.longdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayFp64 = Annotated[
+Np3DArrayFp64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.float64]],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayFp32 = Annotated[
+Np3DArrayFp32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.float32]],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayFp16 = Annotated[
+Np3DArrayFp16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.float16]],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayComplexLongDouble = Annotated[
+Np3DArrayComplexLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.clongdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayComplex128 = Annotated[
+Np3DArrayComplex128: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.complex128]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayComplex64 = Annotated[
+Np3DArrayComplex64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.complex64]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayBool = Annotated[
+Np3DArrayBool: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.bool_]],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayDatetime64 = Annotated[
+Np3DArrayDatetime64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.datetime64]],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=3, strict_data_typing=True),
 ]
 
-NpStrict3DArrayTimedelta64 = Annotated[
+Np3DArrayTimedelta64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int, int], np.dtype[np.timedelta64]],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=3, strict_data_typing=True),
 ]
 
 __all__ = [
-    "NpStrict3DArrayInt64",
-    "NpStrict3DArrayInt32",
-    "NpStrict3DArrayInt16",
-    "NpStrict3DArrayInt8",
-    "NpStrict3DArrayUint64",
-    "NpStrict3DArrayUint32",
-    "NpStrict3DArrayUint16",
-    "NpStrict3DArrayUint8",
-    "NpStrict3DArrayFpLongDouble",
-    "NpStrict3DArrayFp64",
-    "NpStrict3DArrayFp32",
-    "NpStrict3DArrayFp16",
-    "NpStrict3DArrayComplexLongDouble",
-    "NpStrict3DArrayComplex128",
-    "NpStrict3DArrayComplex64",
-    "NpStrict3DArrayBool",
-    "NpStrict3DArrayDatetime64",
-    "NpStrict3DArrayTimedelta64",
+    "Np3DArray",
+    "Np3DArrayInt64",
+    "Np3DArrayInt32",
+    "Np3DArrayInt16",
+    "Np3DArrayInt8",
+    "Np3DArrayUint64",
+    "Np3DArrayUint32",
+    "Np3DArrayUint16",
+    "Np3DArrayUint8",
+    "Np3DArrayFpLongDouble",
+    "Np3DArrayFp64",
+    "Np3DArrayFp32",
+    "Np3DArrayFp16",
+    "Np3DArrayComplexLongDouble",
+    "Np3DArrayComplex128",
+    "Np3DArrayComplex64",
+    "Np3DArrayBool",
+    "Np3DArrayDatetime64",
+    "Np3DArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/strict_data_type/n_dimensional.py b/pydantic_numpy/typing/type_safe/n_dimensional.py
similarity index 66%
rename from pydantic_numpy/typing/strict_data_type/n_dimensional.py
rename to pydantic_numpy/typing/type_safe/n_dimensional.py
index 500471c..a58a4ec 100644
--- a/pydantic_numpy/typing/strict_data_type/n_dimensional.py
+++ b/pydantic_numpy/typing/type_safe/n_dimensional.py
@@ -1,116 +1,122 @@
-from typing import Annotated, Any
+from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
-NpStrictNDArrayInt64 = Annotated[
+NpNDArray: TypeAlias = Annotated[
+    np.ndarray[Any, np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(data_type=None, dimensions=None, strict_data_typing=False),
+]
+
+NpNDArrayInt64: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.int64]],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayInt32 = Annotated[
+NpNDArrayInt32: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.int32]],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayInt16 = Annotated[
+NpNDArrayInt16: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.int16]],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayInt8 = Annotated[
+NpNDArrayInt8: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.int8]],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayUint64 = Annotated[
+NpNDArrayUint64: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.uint64]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayUint32 = Annotated[
+NpNDArrayUint32: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.uint32]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayUint16 = Annotated[
+NpNDArrayUint16: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.uint16]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayUint8 = Annotated[
+NpNDArrayUint8: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.uint8]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayFpLongDouble = Annotated[
+NpNDArrayFpLongDouble: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.longdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayFp64 = Annotated[
+NpNDArrayFp64: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.float64]],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayFp32 = Annotated[
+NpNDArrayFp32: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.float32]],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayFp16 = Annotated[
+NpNDArrayFp16: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.float16]],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayComplexLongDouble = Annotated[
+NpNDArrayComplexLongDouble: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.clongdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayComplex128 = Annotated[
+NpNDArrayComplex128: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.complex128]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayComplex64 = Annotated[
+NpNDArrayComplex64: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.complex64]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayBool = Annotated[
+NpNDArrayBool: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.bool_]],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayDatetime64 = Annotated[
+NpNDArrayDatetime64: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.datetime64]],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=None, strict_data_typing=True),
 ]
 
-NpStrictNDArrayTimedelta64 = Annotated[
+NpNDArrayTimedelta64: TypeAlias = Annotated[
     np.ndarray[Any, np.dtype[np.timedelta64]],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=None, strict_data_typing=True),
 ]
 
 __all__ = [
-    "NpStrictNDArrayInt64",
-    "NpStrictNDArrayInt32",
-    "NpStrictNDArrayInt16",
-    "NpStrictNDArrayInt8",
-    "NpStrictNDArrayUint64",
-    "NpStrictNDArrayUint32",
-    "NpStrictNDArrayUint16",
-    "NpStrictNDArrayUint8",
-    "NpStrictNDArrayFpLongDouble",
-    "NpStrictNDArrayFp64",
-    "NpStrictNDArrayFp32",
-    "NpStrictNDArrayFp16",
-    "NpStrictNDArrayComplexLongDouble",
-    "NpStrictNDArrayComplex128",
-    "NpStrictNDArrayComplex64",
-    "NpStrictNDArrayBool",
-    "NpStrictNDArrayDatetime64",
-    "NpStrictNDArrayTimedelta64",
+    "NpNDArray",
+    "NpNDArrayInt64",
+    "NpNDArrayInt32",
+    "NpNDArrayInt16",
+    "NpNDArrayInt8",
+    "NpNDArrayUint64",
+    "NpNDArrayUint32",
+    "NpNDArrayUint16",
+    "NpNDArrayUint8",
+    "NpNDArrayFpLongDouble",
+    "NpNDArrayFp64",
+    "NpNDArrayFp32",
+    "NpNDArrayFp16",
+    "NpNDArrayComplexLongDouble",
+    "NpNDArrayComplex128",
+    "NpNDArrayComplex64",
+    "NpNDArrayBool",
+    "NpNDArrayDatetime64",
+    "NpNDArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/with_loader/__init__.py b/pydantic_numpy/typing/with_loader/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/pydantic_numpy/typing/i_dimensional.py b/pydantic_numpy/typing/with_loader/i_dimensional.py
similarity index 71%
rename from pydantic_numpy/typing/i_dimensional.py
rename to pydantic_numpy/typing/with_loader/i_dimensional.py
index 5740134..a648128 100644
--- a/pydantic_numpy/typing/i_dimensional.py
+++ b/pydantic_numpy/typing/with_loader/i_dimensional.py
@@ -1,4 +1,4 @@
-from typing import Annotated, Any, Union
+from typing import Annotated, Any, TypeAlias, Union
 
 import numpy as np
 from pydantic import FilePath
@@ -6,119 +6,119 @@
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 from pydantic_numpy.model import MultiArrayNumpyFile
 
-Np1DArray = Annotated[
+NpLoading1DArray: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[Any]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=None, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayInt64 = Annotated[
+NpLoading1DArrayInt64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.int64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayInt32 = Annotated[
+NpLoading1DArrayInt32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.int32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayInt16 = Annotated[
+NpLoading1DArrayInt16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.int16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayInt8 = Annotated[
+NpLoading1DArrayInt8: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.int8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayUint64 = Annotated[
+NpLoading1DArrayUint64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.uint64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayUint32 = Annotated[
+NpLoading1DArrayUint32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.uint32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayUint16 = Annotated[
+NpLoading1DArrayUint16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.uint16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayUint8 = Annotated[
+NpLoading1DArrayUint8: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.uint8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayFpLongDouble = Annotated[
+NpLoading1DArrayFpLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.longdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayFp64 = Annotated[
+NpLoading1DArrayFp64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.float64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayFp32 = Annotated[
+NpLoading1DArrayFp32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.float32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayFp16 = Annotated[
+NpLoading1DArrayFp16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.float16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayComplexLongDouble = Annotated[
+NpLoading1DArrayComplexLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.clongdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayComplex128 = Annotated[
+NpLoading1DArrayComplex128: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.complex128]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayComplex64 = Annotated[
+NpLoading1DArrayComplex64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.complex64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayBool = Annotated[
+NpLoading1DArrayBool: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.bool_]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayDatetime64 = Annotated[
+NpLoading1DArrayDatetime64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.datetime64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=1, strict_data_typing=False),
 ]
 
-Np1DArrayTimedelta64 = Annotated[
+NpLoading1DArrayTimedelta64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int], np.dtype[np.timedelta64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=1, strict_data_typing=False),
 ]
 
 __all__ = [
-    "Np1DArray",
-    "Np1DArrayInt64",
-    "Np1DArrayInt32",
-    "Np1DArrayInt16",
-    "Np1DArrayInt8",
-    "Np1DArrayUint64",
-    "Np1DArrayUint32",
-    "Np1DArrayUint16",
-    "Np1DArrayUint8",
-    "Np1DArrayFpLongDouble",
-    "Np1DArrayFp64",
-    "Np1DArrayFp32",
-    "Np1DArrayFp16",
-    "Np1DArrayComplexLongDouble",
-    "Np1DArrayComplex128",
-    "Np1DArrayComplex64",
-    "Np1DArrayBool",
-    "Np1DArrayDatetime64",
-    "Np1DArrayTimedelta64",
+    "NpLoading1DArray",
+    "NpLoading1DArrayInt64",
+    "NpLoading1DArrayInt32",
+    "NpLoading1DArrayInt16",
+    "NpLoading1DArrayInt8",
+    "NpLoading1DArrayUint64",
+    "NpLoading1DArrayUint32",
+    "NpLoading1DArrayUint16",
+    "NpLoading1DArrayUint8",
+    "NpLoading1DArrayFpLongDouble",
+    "NpLoading1DArrayFp64",
+    "NpLoading1DArrayFp32",
+    "NpLoading1DArrayFp16",
+    "NpLoading1DArrayComplexLongDouble",
+    "NpLoading1DArrayComplex128",
+    "NpLoading1DArrayComplex64",
+    "NpLoading1DArrayBool",
+    "NpLoading1DArrayDatetime64",
+    "NpLoading1DArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/ii_dimensional.py b/pydantic_numpy/typing/with_loader/ii_dimensional.py
similarity index 71%
rename from pydantic_numpy/typing/ii_dimensional.py
rename to pydantic_numpy/typing/with_loader/ii_dimensional.py
index d1b9b6b..f71907d 100644
--- a/pydantic_numpy/typing/ii_dimensional.py
+++ b/pydantic_numpy/typing/with_loader/ii_dimensional.py
@@ -1,4 +1,4 @@
-from typing import Annotated, Any, Union
+from typing import Annotated, Any, TypeAlias, Union
 
 import numpy as np
 from pydantic import FilePath
@@ -6,119 +6,119 @@
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 from pydantic_numpy.model import MultiArrayNumpyFile
 
-Np2DArray = Annotated[
+NpLoading2DArray: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[Any]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=None, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayInt64 = Annotated[
+NpLoading2DArrayInt64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.int64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayInt32 = Annotated[
+NpLoading2DArrayInt32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.int32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayInt16 = Annotated[
+NpLoading2DArrayInt16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.int16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayInt8 = Annotated[
+NpLoading2DArrayInt8: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.int8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayUint64 = Annotated[
+NpLoading2DArrayUint64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.uint64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayUint32 = Annotated[
+NpLoading2DArrayUint32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.uint32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayUint16 = Annotated[
+NpLoading2DArrayUint16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.uint16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayUint8 = Annotated[
+NpLoading2DArrayUint8: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.uint8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayFpLongDouble = Annotated[
+NpLoading2DArrayFpLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.longdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayFp64 = Annotated[
+NpLoading2DArrayFp64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.float64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayFp32 = Annotated[
+NpLoading2DArrayFp32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.float32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayFp16 = Annotated[
+NpLoading2DArrayFp16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.float16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayComplexLongDouble = Annotated[
+NpLoading2DArrayComplexLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.clongdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayComplex128 = Annotated[
+NpLoading2DArrayComplex128: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.complex128]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayComplex64 = Annotated[
+NpLoading2DArrayComplex64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.complex64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayBool = Annotated[
+NpLoading2DArrayBool: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.bool_]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayDatetime64 = Annotated[
+NpLoading2DArrayDatetime64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.datetime64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=2, strict_data_typing=False),
 ]
 
-Np2DArrayTimedelta64 = Annotated[
+NpLoading2DArrayTimedelta64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int], np.dtype[np.timedelta64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=2, strict_data_typing=False),
 ]
 
 __all__ = [
-    "Np2DArray",
-    "Np2DArrayInt64",
-    "Np2DArrayInt32",
-    "Np2DArrayInt16",
-    "Np2DArrayInt8",
-    "Np2DArrayUint64",
-    "Np2DArrayUint32",
-    "Np2DArrayUint16",
-    "Np2DArrayUint8",
-    "Np2DArrayFpLongDouble",
-    "Np2DArrayFp64",
-    "Np2DArrayFp32",
-    "Np2DArrayFp16",
-    "Np2DArrayComplexLongDouble",
-    "Np2DArrayComplex128",
-    "Np2DArrayComplex64",
-    "Np2DArrayBool",
-    "Np2DArrayDatetime64",
-    "Np2DArrayTimedelta64",
+    "NpLoading2DArray",
+    "NpLoading2DArrayInt64",
+    "NpLoading2DArrayInt32",
+    "NpLoading2DArrayInt16",
+    "NpLoading2DArrayInt8",
+    "NpLoading2DArrayUint64",
+    "NpLoading2DArrayUint32",
+    "NpLoading2DArrayUint16",
+    "NpLoading2DArrayUint8",
+    "NpLoading2DArrayFpLongDouble",
+    "NpLoading2DArrayFp64",
+    "NpLoading2DArrayFp32",
+    "NpLoading2DArrayFp16",
+    "NpLoading2DArrayComplexLongDouble",
+    "NpLoading2DArrayComplex128",
+    "NpLoading2DArrayComplex64",
+    "NpLoading2DArrayBool",
+    "NpLoading2DArrayDatetime64",
+    "NpLoading2DArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/iii_dimensional.py b/pydantic_numpy/typing/with_loader/iii_dimensional.py
similarity index 72%
rename from pydantic_numpy/typing/iii_dimensional.py
rename to pydantic_numpy/typing/with_loader/iii_dimensional.py
index ebc665a..ede5816 100644
--- a/pydantic_numpy/typing/iii_dimensional.py
+++ b/pydantic_numpy/typing/with_loader/iii_dimensional.py
@@ -1,4 +1,4 @@
-from typing import Annotated, Any, Union
+from typing import Annotated, Any, TypeAlias, Union
 
 import numpy as np
 from pydantic import FilePath
@@ -6,119 +6,119 @@
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 from pydantic_numpy.model import MultiArrayNumpyFile
 
-Np3DArray = Annotated[
+NpLoading3DArray: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[Any]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=None, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayInt64 = Annotated[
+NpLoading3DArrayInt64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.int64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayInt32 = Annotated[
+NpLoading3DArrayInt32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.int32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayInt16 = Annotated[
+NpLoading3DArrayInt16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.int16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayInt8 = Annotated[
+NpLoading3DArrayInt8: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.int8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayUint64 = Annotated[
+NpLoading3DArrayUint64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.uint64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayUint32 = Annotated[
+NpLoading3DArrayUint32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.uint32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayUint16 = Annotated[
+NpLoading3DArrayUint16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.uint16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayUint8 = Annotated[
+NpLoading3DArrayUint8: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.uint8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayFpLongDouble = Annotated[
+NpLoading3DArrayFpLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.longdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayFp64 = Annotated[
+NpLoading3DArrayFp64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.float64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayFp32 = Annotated[
+NpLoading3DArrayFp32: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.float32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayFp16 = Annotated[
+NpLoading3DArrayFp16: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.float16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayComplexLongDouble = Annotated[
+NpLoading3DArrayComplexLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.clongdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayComplex128 = Annotated[
+NpLoading3DArrayComplex128: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.complex128]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayComplex64 = Annotated[
+NpLoading3DArrayComplex64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.complex64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayBool = Annotated[
+NpLoading3DArrayBool: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.bool_]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayDatetime64 = Annotated[
+NpLoading3DArrayDatetime64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.datetime64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=3, strict_data_typing=False),
 ]
 
-Np3DArrayTimedelta64 = Annotated[
+NpLoading3DArrayTimedelta64: TypeAlias = Annotated[
     Union[np.ndarray[tuple[int, int, int], np.dtype[np.timedelta64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=3, strict_data_typing=False),
 ]
 
 __all__ = [
-    "Np3DArray",
-    "Np3DArrayInt64",
-    "Np3DArrayInt32",
-    "Np3DArrayInt16",
-    "Np3DArrayInt8",
-    "Np3DArrayUint64",
-    "Np3DArrayUint32",
-    "Np3DArrayUint16",
-    "Np3DArrayUint8",
-    "Np3DArrayFpLongDouble",
-    "Np3DArrayFp64",
-    "Np3DArrayFp32",
-    "Np3DArrayFp16",
-    "Np3DArrayComplexLongDouble",
-    "Np3DArrayComplex128",
-    "Np3DArrayComplex64",
-    "Np3DArrayBool",
-    "Np3DArrayDatetime64",
-    "Np3DArrayTimedelta64",
+    "NpLoading3DArray",
+    "NpLoading3DArrayInt64",
+    "NpLoading3DArrayInt32",
+    "NpLoading3DArrayInt16",
+    "NpLoading3DArrayInt8",
+    "NpLoading3DArrayUint64",
+    "NpLoading3DArrayUint32",
+    "NpLoading3DArrayUint16",
+    "NpLoading3DArrayUint8",
+    "NpLoading3DArrayFpLongDouble",
+    "NpLoading3DArrayFp64",
+    "NpLoading3DArrayFp32",
+    "NpLoading3DArrayFp16",
+    "NpLoading3DArrayComplexLongDouble",
+    "NpLoading3DArrayComplex128",
+    "NpLoading3DArrayComplex64",
+    "NpLoading3DArrayBool",
+    "NpLoading3DArrayDatetime64",
+    "NpLoading3DArrayTimedelta64",
 ]
diff --git a/pydantic_numpy/typing/n_dimensional.py b/pydantic_numpy/typing/with_loader/n_dimensional.py
similarity index 70%
rename from pydantic_numpy/typing/n_dimensional.py
rename to pydantic_numpy/typing/with_loader/n_dimensional.py
index af4f9f4..27b8bcb 100644
--- a/pydantic_numpy/typing/n_dimensional.py
+++ b/pydantic_numpy/typing/with_loader/n_dimensional.py
@@ -1,4 +1,4 @@
-from typing import Annotated, Any, Union
+from typing import Annotated, Any, TypeAlias, Union
 
 import numpy as np
 from pydantic import FilePath
@@ -6,119 +6,119 @@
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 from pydantic_numpy.model import MultiArrayNumpyFile
 
-NpNDArray = Annotated[
+NpLoadingNDArray: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[Any]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=None, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayInt64 = Annotated[
+NpLoadingNDArrayInt64: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.int64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayInt32 = Annotated[
+NpLoadingNDArrayInt32: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.int32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayInt16 = Annotated[
+NpLoadingNDArrayInt16: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.int16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayInt8 = Annotated[
+NpLoadingNDArrayInt8: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.int8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayUint64 = Annotated[
+NpLoadingNDArrayUint64: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.uint64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayUint32 = Annotated[
+NpLoadingNDArrayUint32: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.uint32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayUint16 = Annotated[
+NpLoadingNDArrayUint16: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.uint16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayUint8 = Annotated[
+NpLoadingNDArrayUint8: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.uint8]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayFpLongDouble = Annotated[
+NpLoadingNDArrayFpLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.longdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayFp64 = Annotated[
+NpLoadingNDArrayFp64: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.float64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayFp32 = Annotated[
+NpLoadingNDArrayFp32: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.float32]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayFp16 = Annotated[
+NpLoadingNDArrayFp16: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.float16]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayComplexLongDouble = Annotated[
+NpLoadingNDArrayComplexLongDouble: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.clongdouble]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayComplex128 = Annotated[
+NpLoadingNDArrayComplex128: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.complex128]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayComplex64 = Annotated[
+NpLoadingNDArrayComplex64: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.complex64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayBool = Annotated[
+NpLoadingNDArrayBool: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.bool_]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayDatetime64 = Annotated[
+NpLoadingNDArrayDatetime64: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.datetime64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=None, strict_data_typing=False),
 ]
 
-NpNDArrayTimedelta64 = Annotated[
+NpLoadingNDArrayTimedelta64: TypeAlias = Annotated[
     Union[np.ndarray[Any, np.dtype[np.timedelta64]], FilePath, MultiArrayNumpyFile],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=None, strict_data_typing=False),
 ]
 
 __all__ = [
-    "NpNDArray",
-    "NpNDArrayInt64",
-    "NpNDArrayInt32",
-    "NpNDArrayInt16",
-    "NpNDArrayInt8",
-    "NpNDArrayUint64",
-    "NpNDArrayUint32",
-    "NpNDArrayUint16",
-    "NpNDArrayUint8",
-    "NpNDArrayFpLongDouble",
-    "NpNDArrayFp64",
-    "NpNDArrayFp32",
-    "NpNDArrayFp16",
-    "NpNDArrayComplexLongDouble",
-    "NpNDArrayComplex128",
-    "NpNDArrayComplex64",
-    "NpNDArrayBool",
-    "NpNDArrayDatetime64",
-    "NpNDArrayTimedelta64",
+    "NpLoadingNDArray",
+    "NpLoadingNDArrayInt64",
+    "NpLoadingNDArrayInt32",
+    "NpLoadingNDArrayInt16",
+    "NpLoadingNDArrayInt8",
+    "NpLoadingNDArrayUint64",
+    "NpLoadingNDArrayUint32",
+    "NpLoadingNDArrayUint16",
+    "NpLoadingNDArrayUint8",
+    "NpLoadingNDArrayFpLongDouble",
+    "NpLoadingNDArrayFp64",
+    "NpLoadingNDArrayFp32",
+    "NpLoadingNDArrayFp16",
+    "NpLoadingNDArrayComplexLongDouble",
+    "NpLoadingNDArrayComplex128",
+    "NpLoadingNDArrayComplex64",
+    "NpLoadingNDArrayBool",
+    "NpLoadingNDArrayDatetime64",
+    "NpLoadingNDArrayTimedelta64",
 ]
diff --git a/pyproject.toml b/pyproject.toml
index 94720d6..a67592c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,12 +1,12 @@
 [tool.poetry]
 name = "pydantic_numpy"
-version = "7.0.0"
+version = "8.0.0"
 description = "Pydantic Model integration of the NumPy array"
 authors = ["Can H. Tartanoglu", "Christoph Heindl"]
 maintainers = ["Can H. Tartanoglu <python@rotas.mozmail.com>"]
 readme = "README.md"
 homepage = "https://github.com/caniko/pydantic-numpy"
-license = "BSD-4"
+license = "BSD-3-Clause"
 
 keywords = ["pydantic", "numpy", "typing", "validation"]
 classifiers = [
@@ -22,7 +22,7 @@ python = ">=3.10,<3.14"
 compress-pickle = { version = "*", extras = ["lz4"] }
 ruamel-yaml = "^0.18.5"
 
-numpy = ">=2.0.0"
+numpy = "^2"
 pydantic = "^2.0"
 semver = "^3.0.1"
 
diff --git a/tests/helper/testing_groups.py b/tests/helper/testing_groups.py
index da17945..dbdd582 100644
--- a/tests/helper/testing_groups.py
+++ b/tests/helper/testing_groups.py
@@ -103,80 +103,80 @@
 ]
 
 # Data type strict
-strict_data_type_1d_array_typing_dimensions = [
-    (np.array([0]), np.int64, NpStrict1DArrayInt64, 1),
-    (np.array([0], dtype=np.int32), np.int32, NpStrict1DArrayInt32, 1),
-    (np.array([0], dtype=np.int16), np.int16, NpStrict1DArrayInt16, 1),
-    (np.array([0], dtype=np.int8), np.int8, NpStrict1DArrayInt8, 1),
-    (np.array([0], dtype=np.uint64), np.uint64, NpStrict1DArrayUint64, 1),
-    (np.array([0], dtype=np.uint32), np.uint32, NpStrict1DArrayUint32, 1),
-    (np.array([0], dtype=np.uint16), np.uint16, NpStrict1DArrayUint16, 1),
-    (np.array([0], dtype=np.uint8), np.uint8, NpStrict1DArrayUint8, 1),
-    (np.array([0.0]), np.float64, NpStrict1DArrayFp64, 1),
-    (np.array([0.0], dtype=np.float32), np.float32, NpStrict1DArrayFp32, 1),
-    (np.array([0.0], dtype=np.float16), np.float16, NpStrict1DArrayFp16, 1),
-    (np.array([0.0 + 0.0j]), np.complex128, NpStrict1DArrayComplex128, 1),
-    (np.array([0.0 + 0.0j], dtype=np.complex64), np.complex64, NpStrict1DArrayComplex64, 1),
-    (np.array([False]), np.bool_, NpStrict1DArrayBool, 1),
-    (np.array([0], dtype=np.timedelta64), np.timedelta64, NpStrict1DArrayTimedelta64, 1),
+type_safe_data_type_1d_array_typing_dimensions = [
+    (np.array([0]), np.int64, Np1DArrayInt64, 1),
+    (np.array([0], dtype=np.int32), np.int32, Np1DArrayInt32, 1),
+    (np.array([0], dtype=np.int16), np.int16, Np1DArrayInt16, 1),
+    (np.array([0], dtype=np.int8), np.int8, Np1DArrayInt8, 1),
+    (np.array([0], dtype=np.uint64), np.uint64, Np1DArrayUint64, 1),
+    (np.array([0], dtype=np.uint32), np.uint32, Np1DArrayUint32, 1),
+    (np.array([0], dtype=np.uint16), np.uint16, Np1DArrayUint16, 1),
+    (np.array([0], dtype=np.uint8), np.uint8, Np1DArrayUint8, 1),
+    (np.array([0.0]), np.float64, Np1DArrayFp64, 1),
+    (np.array([0.0], dtype=np.float32), np.float32, Np1DArrayFp32, 1),
+    (np.array([0.0], dtype=np.float16), np.float16, Np1DArrayFp16, 1),
+    (np.array([0.0 + 0.0j]), np.complex128, Np1DArrayComplex128, 1),
+    (np.array([0.0 + 0.0j], dtype=np.complex64), np.complex64, Np1DArrayComplex64, 1),
+    (np.array([False]), np.bool_, Np1DArrayBool, 1),
+    (np.array([0], dtype=np.timedelta64), np.timedelta64, Np1DArrayTimedelta64, 1),
 ]
-strict_data_type_2d_array_typing_dimensions = [
-    (np.array([[0]]), np.int64, NpStrict2DArrayInt64, 2),
-    (np.array([[0]], dtype=np.int32), np.int32, NpStrict2DArrayInt32, 2),
-    (np.array([[0]], dtype=np.int16), np.int16, NpStrict2DArrayInt16, 2),
-    (np.array([[0]], dtype=np.int8), np.int8, NpStrict2DArrayInt8, 2),
-    (np.array([[0]], dtype=np.uint64), np.uint64, NpStrict2DArrayUint64, 2),
-    (np.array([[0]], dtype=np.uint32), np.uint32, NpStrict2DArrayUint32, 2),
-    (np.array([[0]], dtype=np.uint16), np.uint16, NpStrict2DArrayUint16, 2),
-    (np.array([[0]], dtype=np.uint8), np.uint8, NpStrict2DArrayUint8, 2),
-    (np.array([[0.0]]), np.float64, NpStrict2DArrayFp64, 2),
-    (np.array([[0.0]], dtype=np.float32), np.float32, NpStrict2DArrayFp32, 2),
-    (np.array([[0.0]], dtype=np.float16), np.float16, NpStrict2DArrayFp16, 2),
-    (np.array([[0.0 + 0.0j]]), np.complex128, NpStrict2DArrayComplex128, 2),
-    (np.array([[0.0 + 0.0j]], dtype=np.complex64), np.complex64, NpStrict2DArrayComplex64, 2),
-    (np.array([[False]]), np.bool_, NpStrict2DArrayBool, 2),
-    (np.array([[0]], dtype=np.timedelta64), np.timedelta64, NpStrict2DArrayTimedelta64, 2),
+type_safe_data_type_2d_array_typing_dimensions = [
+    (np.array([[0]]), np.int64, Np2DArrayInt64, 2),
+    (np.array([[0]], dtype=np.int32), np.int32, Np2DArrayInt32, 2),
+    (np.array([[0]], dtype=np.int16), np.int16, Np2DArrayInt16, 2),
+    (np.array([[0]], dtype=np.int8), np.int8, Np2DArrayInt8, 2),
+    (np.array([[0]], dtype=np.uint64), np.uint64, Np2DArrayUint64, 2),
+    (np.array([[0]], dtype=np.uint32), np.uint32, Np2DArrayUint32, 2),
+    (np.array([[0]], dtype=np.uint16), np.uint16, Np2DArrayUint16, 2),
+    (np.array([[0]], dtype=np.uint8), np.uint8, Np2DArrayUint8, 2),
+    (np.array([[0.0]]), np.float64, Np2DArrayFp64, 2),
+    (np.array([[0.0]], dtype=np.float32), np.float32, Np2DArrayFp32, 2),
+    (np.array([[0.0]], dtype=np.float16), np.float16, Np2DArrayFp16, 2),
+    (np.array([[0.0 + 0.0j]]), np.complex128, Np2DArrayComplex128, 2),
+    (np.array([[0.0 + 0.0j]], dtype=np.complex64), np.complex64, Np2DArrayComplex64, 2),
+    (np.array([[False]]), np.bool_, Np2DArrayBool, 2),
+    (np.array([[0]], dtype=np.timedelta64), np.timedelta64, Np2DArrayTimedelta64, 2),
 ]
-strict_data_type_3d_array_typing_dimensions = [
-    (np.array([[[0]]]), np.int64, NpStrict3DArrayInt64, 3),
-    (np.array([[[0]]], dtype=np.int32), np.int32, NpStrict3DArrayInt32, 3),
-    (np.array([[[0]]], dtype=np.int16), np.int16, NpStrict3DArrayInt16, 3),
-    (np.array([[[0]]], dtype=np.int8), np.int8, NpStrict3DArrayInt8, 3),
-    (np.array([[[0]]], dtype=np.uint64), np.uint64, NpStrict3DArrayUint64, 3),
-    (np.array([[[0]]], dtype=np.uint32), np.uint32, NpStrict3DArrayUint32, 3),
-    (np.array([[[0]]], dtype=np.uint16), np.uint16, NpStrict3DArrayUint16, 3),
-    (np.array([[[0]]], dtype=np.uint8), np.uint8, NpStrict3DArrayUint8, 3),
-    (np.array([[[0.0]]]), np.float64, NpStrict3DArrayFp64, 3),
-    (np.array([[[0.0]]], dtype=np.float32), np.float32, NpStrict3DArrayFp32, 3),
-    (np.array([[[0.0]]], dtype=np.float16), np.float16, NpStrict3DArrayFp16, 3),
-    (np.array([[[0.0 + 0.0j]]]), np.complex128, NpStrict3DArrayComplex128, 3),
-    (np.array([[[0.0 + 0.0j]]], dtype=np.complex64), np.complex64, NpStrict3DArrayComplex64, 3),
-    (np.array([[[False]]]), np.bool_, NpStrict3DArrayBool, 3),
-    (np.array([[[0]]], dtype=np.timedelta64), np.timedelta64, NpStrict3DArrayTimedelta64, 3),
+type_safe_data_type_3d_array_typing_dimensions = [
+    (np.array([[[0]]]), np.int64, Np3DArrayInt64, 3),
+    (np.array([[[0]]], dtype=np.int32), np.int32, Np3DArrayInt32, 3),
+    (np.array([[[0]]], dtype=np.int16), np.int16, Np3DArrayInt16, 3),
+    (np.array([[[0]]], dtype=np.int8), np.int8, Np3DArrayInt8, 3),
+    (np.array([[[0]]], dtype=np.uint64), np.uint64, Np3DArrayUint64, 3),
+    (np.array([[[0]]], dtype=np.uint32), np.uint32, Np3DArrayUint32, 3),
+    (np.array([[[0]]], dtype=np.uint16), np.uint16, Np3DArrayUint16, 3),
+    (np.array([[[0]]], dtype=np.uint8), np.uint8, Np3DArrayUint8, 3),
+    (np.array([[[0.0]]]), np.float64, Np3DArrayFp64, 3),
+    (np.array([[[0.0]]], dtype=np.float32), np.float32, Np3DArrayFp32, 3),
+    (np.array([[[0.0]]], dtype=np.float16), np.float16, Np3DArrayFp16, 3),
+    (np.array([[[0.0 + 0.0j]]]), np.complex128, Np3DArrayComplex128, 3),
+    (np.array([[[0.0 + 0.0j]]], dtype=np.complex64), np.complex64, Np3DArrayComplex64, 3),
+    (np.array([[[False]]]), np.bool_, Np3DArrayBool, 3),
+    (np.array([[[0]]], dtype=np.timedelta64), np.timedelta64, Np3DArrayTimedelta64, 3),
 ]
-strict_data_type_nd_array_typing_dimensions = [
-    (np.array([0]), np.int64, NpStrictNDArrayInt64, None),
-    (np.array([0], dtype=np.int32), np.int32, NpStrictNDArrayInt32, None),
-    (np.array([0], dtype=np.int16), np.int16, NpStrictNDArrayInt16, None),
-    (np.array([0], dtype=np.int8), np.int8, NpStrictNDArrayInt8, None),
-    (np.array([0], dtype=np.uint64), np.uint64, NpStrictNDArrayUint64, None),
-    (np.array([0], dtype=np.uint32), np.uint32, NpStrictNDArrayUint32, None),
-    (np.array([0], dtype=np.uint16), np.uint16, NpStrictNDArrayUint16, None),
-    (np.array([0], dtype=np.uint8), np.uint8, NpStrictNDArrayUint8, None),
-    (np.array([0.0]), np.float64, NpStrictNDArrayFp64, None),
-    (np.array([0.0], dtype=np.float32), np.float32, NpStrictNDArrayFp32, None),
-    (np.array([0.0], dtype=np.float16), np.float16, NpStrictNDArrayFp16, None),
-    (np.array([0.0 + 0.0j]), np.complex128, NpStrictNDArrayComplex128, None),
-    (np.array([0.0 + 0.0j], dtype=np.complex64), np.complex64, NpStrictNDArrayComplex64, None),
-    (np.array([False]), np.bool_, NpStrictNDArrayBool, None),
-    (np.array([0], dtype=np.timedelta64), np.timedelta64, NpStrictNDArrayTimedelta64, None),
+type_safe_data_type_nd_array_typing_dimensions = [
+    (np.array([0]), np.int64, NpNDArrayInt64, None),
+    (np.array([0], dtype=np.int32), np.int32, NpNDArrayInt32, None),
+    (np.array([0], dtype=np.int16), np.int16, NpNDArrayInt16, None),
+    (np.array([0], dtype=np.int8), np.int8, NpNDArrayInt8, None),
+    (np.array([0], dtype=np.uint64), np.uint64, NpNDArrayUint64, None),
+    (np.array([0], dtype=np.uint32), np.uint32, NpNDArrayUint32, None),
+    (np.array([0], dtype=np.uint16), np.uint16, NpNDArrayUint16, None),
+    (np.array([0], dtype=np.uint8), np.uint8, NpNDArrayUint8, None),
+    (np.array([0.0]), np.float64, NpNDArrayFp64, None),
+    (np.array([0.0], dtype=np.float32), np.float32, NpNDArrayFp32, None),
+    (np.array([0.0], dtype=np.float16), np.float16, NpNDArrayFp16, None),
+    (np.array([0.0 + 0.0j]), np.complex128, NpNDArrayComplex128, None),
+    (np.array([0.0 + 0.0j], dtype=np.complex64), np.complex64, NpNDArrayComplex64, None),
+    (np.array([False]), np.bool_, NpNDArrayBool, None),
+    (np.array([0], dtype=np.timedelta64), np.timedelta64, NpNDArrayTimedelta64, None),
 ]
 
-strict_data_type_array_typing_dimensions = [
-    *strict_data_type_1d_array_typing_dimensions,
-    *strict_data_type_2d_array_typing_dimensions,
-    *strict_data_type_3d_array_typing_dimensions,
-    *strict_data_type_nd_array_typing_dimensions,
+type_safe_data_type_array_typing_dimensions = [
+    *type_safe_data_type_1d_array_typing_dimensions,
+    *type_safe_data_type_2d_array_typing_dimensions,
+    *type_safe_data_type_3d_array_typing_dimensions,
+    *type_safe_data_type_nd_array_typing_dimensions,
 ]
 
 dimension_testing_group = [
@@ -187,8 +187,8 @@
 
 if platform.system() != "Windows":
 
-    def get_strict_data_type_nd_array_typing_dimensions_128_bit():
+    def get_type_safe_data_type_nd_array_typing_dimensions_128_bit():
         return [
-            (np.array([0.0], dtype=np.float128), np.float128, NpStrictNDArrayFpLongDouble, None),
-            (np.array([0.0 + 0.0j], dtype=np.complex256), np.complex256, NpStrictNDArrayComplexLongDouble, None),
+            (np.array([0.0], dtype=np.float128), np.float128, NpNDArrayFpLongDouble, None),
+            (np.array([0.0 + 0.0j], dtype=np.complex256), np.complex256, NpNDArrayComplexLongDouble, None),
         ]
diff --git a/tests/model.py b/tests/model.py
index 2f6fa92..a3af34e 100644
--- a/tests/model.py
+++ b/tests/model.py
@@ -1,6 +1,5 @@
-from pydantic_numpy import NpNDArray
 from pydantic_numpy.model import NumpyModel
-from pydantic_numpy.typing import Np1DArray
+from pydantic_numpy.typing import Np1DArray, NpNDArray
 
 
 class NpNDArrayModel(NumpyModel):
diff --git a/tests/test_annotation.py b/tests/test_annotation.py
index d789149..6be44d6 100644
--- a/tests/test_annotation.py
+++ b/tests/test_annotation.py
@@ -8,19 +8,21 @@
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
 
-def test_custom_serializer():
-    def custom_serializer(array: np.ndarray) -> list[float]:
-        return array.astype(float).tolist()
+def _custom_serializer(array: np.ndarray) -> list[float]:
+    return array.astype(float).tolist()
+
 
-    Np1DArray: TypeAlias = Annotated[
-        np.ndarray[tuple[int], np.dtype[Any]],
-        NpArrayPydanticAnnotation.factory(
-            data_type=None, dimensions=1, strict_data_typing=False, serialize_numpy_array_to_json=custom_serializer
-        ),
-    ]
+_Np1DArray: TypeAlias = Annotated[
+    np.ndarray[tuple[int], np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(
+        data_type=None, dimensions=1, strict_data_typing=False, serialize_numpy_array_to_json=_custom_serializer
+    ),
+]
 
+
+def test_custom_serializer():
     class FooModel(BaseModel):
-        arr: Np1DArray
+        arr: _Np1DArray
 
     foo_model = FooModel(arr=np.zeros(42))
 
diff --git a/tests/test_typing.py b/tests/test_typing.py
index 0d3035d..ad53784 100644
--- a/tests/test_typing.py
+++ b/tests/test_typing.py
@@ -18,8 +18,8 @@
 from tests.helper.testing_groups import (
     data_type_array_typing_dimensions,
     data_type_nd_array_typing_dimensions_without_complex,
-    strict_data_type_nd_array_typing_dimensions,
     supported_data_types,
+    type_safe_data_type_nd_array_typing_dimensions,
 )
 
 
@@ -31,7 +31,7 @@ def test_correct_type(
 
 
 @pytest.mark.parametrize(
-    "numpy_array, numpy_dtype, pydantic_typing, dimensions", strict_data_type_nd_array_typing_dimensions
+    "numpy_array, numpy_dtype, pydantic_typing, dimensions", type_safe_data_type_nd_array_typing_dimensions
 )
 @pytest.mark.parametrize("bad_numpy_array, wrong_numpy_type", supported_data_types)
 def test_wrong_dtype_type(
@@ -56,7 +56,7 @@ def test_wrong_dimension():
 
 if platform.system() == "Linux":
     from tests.helper.testing_groups import (
-        get_strict_data_type_nd_array_typing_dimensions_128_bit,
+        get_type_safe_data_type_nd_array_typing_dimensions_128_bit,
     )
 
     @pytest.mark.parametrize(
@@ -120,7 +120,7 @@ def test_multi_array_numpy_error_on_reading_single_array_file(
 
     @pytest.mark.parametrize(
         "numpy_array, numpy_dtype, pydantic_typing, dimensions",
-        get_strict_data_type_nd_array_typing_dimensions_128_bit(),
+        get_type_safe_data_type_nd_array_typing_dimensions_128_bit(),
     )
     def test_correct_128_bit_type(
         numpy_array: npt.ArrayLike, numpy_dtype: npt.DTypeLike, pydantic_typing, dimensions: Optional[int]
@@ -129,7 +129,7 @@ def test_correct_128_bit_type(
 
     @pytest.mark.parametrize(
         "numpy_array, numpy_dtype, pydantic_typing, dimensions",
-        get_strict_data_type_nd_array_typing_dimensions_128_bit(),
+        get_type_safe_data_type_nd_array_typing_dimensions_128_bit(),
     )
     @pytest.mark.parametrize("bad_numpy_array, wrong_numpy_type", supported_data_types)
     def test_wrong_dtype_128_bit_type(
diff --git a/typegen/generate_typing.py b/typegen/generate_typing.py
index c3910af..62c5d7b 100644
--- a/typegen/generate_typing.py
+++ b/typegen/generate_typing.py
@@ -18,7 +18,7 @@ def write_annotations(output_folder: Path, strict: bool) -> None:
     -------
     None
     """
-    generate_template = _generate_strict_template if strict else _generate_union_template
+    generate_template = _generate_type_safe_template if strict else _generate_union_template
     for dimensions in _DIMENSION_TYPES:
         contents = "\n".join(_annotate_type(dimensions, type_name, strict) for type_name in _DATA_TYPES)
         all_types = "\n".join(
@@ -30,7 +30,7 @@ def write_annotations(output_folder: Path, strict: bool) -> None:
             f.write(generate_template(dimensions, contents, all_types))
 
 
-_DATA_TYPES: Final = {
+_DATA_TYPES: Final[dict[str, str]] = {
     "": "None",
     "Int64": "np.int64",
     "Int32": "np.int32",
@@ -52,28 +52,28 @@ def write_annotations(output_folder: Path, strict: bool) -> None:
     "Timedelta64": "np.timedelta64",
 }
 
-_DIMENSION_TYPES: Final = {
+_DIMENSION_TYPES: Final[dict[int, str]] = {
     0: "Any",
     1: "tuple[int]",
     2: "tuple[int, int]",
     3: "tuple[int, int, int]",
 }
 
-_DIMENSIONS_TO_PREFIX: Final = {
+_DIMENSIONS_TO_PREFIX: Final[dict[int, str]] = {
     0: "NDArray",
     1: "1DArray",
     2: "2DArray",
     3: "3DArray",
 }
 
-_DIMENSIONS_TO_FILENAME: Final = {
+_DIMENSIONS_TO_FILENAME: Final[dict[int, str]] = {
     0: "n_dimensional.py",
     1: "i_dimensional.py",
     2: "ii_dimensional.py",
     3: "iii_dimensional.py",
 }
 
-_SPACES: Final = "    "
+_SPACES: Final[str] = "    "
 
 
 def _unindent(text: str) -> str:
@@ -89,7 +89,7 @@ def _quote(text: str) -> str:
 
 
 def _type_name_with_prefix(dimensions: int, type_name: str, strict: bool) -> str:
-    strict_prefix = "Strict" if strict else ""
+    strict_prefix = "" if strict else "Loading"
     dimension_prefix = _DIMENSIONS_TO_PREFIX[dimensions]
     return f"Np{strict_prefix}{dimension_prefix}{type_name}"
 
@@ -106,23 +106,20 @@ def _annotate_type(dimensions: int, type_name: str, strict: bool) -> str:
     dimension_type = _DIMENSION_TYPES[dimensions]
     type_with_prefix = _type_name_with_prefix(dimensions, type_name, strict)
     data_type = _DATA_TYPES[type_name]
-    if data_type == "None" and strict:
-        return ""
 
     dtype = "Any" if data_type == "None" else data_type
     T = _strict_type(dimension_type, dtype) if strict else _union_type(dimension_type, dtype)
     dim = dimensions if dimensions > 0 else None
-    annotation = f"""{type_with_prefix} = Annotated[
+    annotation = f"""{type_with_prefix}: TypeAlias = Annotated[
         {T},
-        NpArrayPydanticAnnotation.factory(data_type={data_type}, dimensions={dim}, strict_data_typing={strict}),
+        NpArrayPydanticAnnotation.factory(data_type={data_type}, dimensions={dim}, strict_data_typing={data_type != "None" and strict}),
     ]
 """
     return _unindent(annotation)
 
 
-def _generate_strict_template(dimensions: int, contents: str, all_types: str) -> str:
-    from_typing = "from typing import Annotated, Any" if dimensions == 0 else "from typing import Annotated"
-    template = f"""{from_typing}
+def _generate_type_safe_template(dimensions: int, contents: str, all_types: str) -> str:
+    template = f"""from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
@@ -138,7 +135,7 @@ def _generate_strict_template(dimensions: int, contents: str, all_types: str) ->
 
 
 def _generate_union_template(dimensions: int, contents: str, all_types: str) -> str:
-    template = f"""from typing import Annotated, Any, Union
+    template = f"""from typing import Annotated, Any, TypeAlias, Union
 
 import numpy as np
 from pydantic import FilePath
@@ -156,13 +153,9 @@ def _generate_union_template(dimensions: int, contents: str, all_types: str) ->
 
 
 def _list_all_types(dimensions: int, strict: bool) -> list[str]:
-    return [
-        _type_name_with_prefix(dimensions, type_name, strict)
-        for type_name in _DATA_TYPES
-        if not (type_name == "" and strict)
-    ]
+    return [_type_name_with_prefix(dimensions, type_name, strict) for type_name in _DATA_TYPES]
 
 
 if __name__ == "__main__":
-    write_annotations(Path("pydantic_numpy/typing"), strict=False)
-    write_annotations(Path("pydantic_numpy/typing/strict_data_type"), strict=True)
+    write_annotations(Path("pydantic_numpy/typing/with_loader"), strict=False)
+    write_annotations(Path("pydantic_numpy/typing/type_safe"), strict=True)