diff --git a/pyproject.toml b/pyproject.toml
index df8b8891776..dc393ed6708 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -117,7 +117,6 @@ ignore = [
     "D104",   # todo: Missing docstring in public package
     "D107",   # Missing docstring in `__init__`
     "ANN101", # Missing type annotation for `self` in method
-    "ANN102", # Missing type annotation for `cls` in classmethod
     "S301",   # todo: `pickle` and modules that wrap it can be unsafe when used to deserialize untrusted data, possible security issue  # todo
     "S310",   # todo: Audit URL open for permitted schemes. Allowing use of `file:` or custom schemes is often unexpected.  # todo
     "B905",   # todo: `zip()` without an explicit `strict=` parameter
diff --git a/src/torchmetrics/classification/accuracy.py b/src/torchmetrics/classification/accuracy.py
index 117a89cb667..6c84ec47b97 100644
--- a/src/torchmetrics/classification/accuracy.py
+++ b/src/torchmetrics/classification/accuracy.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -484,7 +484,7 @@ class Accuracy(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["Accuracy"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/auroc.py b/src/torchmetrics/classification/auroc.py
index 428c961ec1d..4e7c3edf982 100644
--- a/src/torchmetrics/classification/auroc.py
+++ b/src/torchmetrics/classification/auroc.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -502,7 +502,7 @@ class AUROC(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["AUROC"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/average_precision.py b/src/torchmetrics/classification/average_precision.py
index 569c00b73d8..be025da5d02 100644
--- a/src/torchmetrics/classification/average_precision.py
+++ b/src/torchmetrics/classification/average_precision.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -512,7 +512,7 @@ class AveragePrecision(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["AveragePrecision"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/calibration_error.py b/src/torchmetrics/classification/calibration_error.py
index d939bf99daa..aaf4794ec3f 100644
--- a/src/torchmetrics/classification/calibration_error.py
+++ b/src/torchmetrics/classification/calibration_error.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Union
+from typing import Any, List, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -368,7 +368,7 @@ class CalibrationError(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["CalibrationError"],
         task: Literal["binary", "multiclass"],
         n_bins: int = 15,
         norm: Literal["l1", "l2", "max"] = "l1",
diff --git a/src/torchmetrics/classification/cohen_kappa.py b/src/torchmetrics/classification/cohen_kappa.py
index 213fa261ea3..431af8325ee 100644
--- a/src/torchmetrics/classification/cohen_kappa.py
+++ b/src/torchmetrics/classification/cohen_kappa.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -312,7 +312,7 @@ class labels.
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["CohenKappa"],
         task: Literal["binary", "multiclass"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/confusion_matrix.py b/src/torchmetrics/classification/confusion_matrix.py
index b01007cfd94..e1d74c79bc0 100644
--- a/src/torchmetrics/classification/confusion_matrix.py
+++ b/src/torchmetrics/classification/confusion_matrix.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional
+from typing import Any, List, Optional, Type
 
 import torch
 from torch import Tensor
@@ -505,7 +505,7 @@ class ConfusionMatrix(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["ConfusionMatrix"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/exact_match.py b/src/torchmetrics/classification/exact_match.py
index 20ab5344373..7679bb3eab2 100644
--- a/src/torchmetrics/classification/exact_match.py
+++ b/src/torchmetrics/classification/exact_match.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 import torch
 from torch import Tensor
@@ -393,7 +393,7 @@ class ExactMatch(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["ExactMatch"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/f_beta.py b/src/torchmetrics/classification/f_beta.py
index 0386a8b2eb9..48098a7d0dd 100644
--- a/src/torchmetrics/classification/f_beta.py
+++ b/src/torchmetrics/classification/f_beta.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -1053,7 +1053,7 @@ class FBetaScore(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["FBetaScore"],
         task: Literal["binary", "multiclass", "multilabel"],
         beta: float = 1.0,
         threshold: float = 0.5,
@@ -1115,7 +1115,7 @@ class F1Score(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["F1Score"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/hamming.py b/src/torchmetrics/classification/hamming.py
index 340a647aa8d..6b3bacd45c7 100644
--- a/src/torchmetrics/classification/hamming.py
+++ b/src/torchmetrics/classification/hamming.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -493,7 +493,7 @@ class HammingDistance(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["HammingDistance"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/hinge.py b/src/torchmetrics/classification/hinge.py
index 0530fd60c81..fbdf3ada50a 100644
--- a/src/torchmetrics/classification/hinge.py
+++ b/src/torchmetrics/classification/hinge.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 import torch
 from torch import Tensor
@@ -351,7 +351,7 @@ class HingeLoss(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["HingeLoss"],
         task: Literal["binary", "multiclass"],
         num_classes: Optional[int] = None,
         squared: bool = False,
diff --git a/src/torchmetrics/classification/jaccard.py b/src/torchmetrics/classification/jaccard.py
index a4f07febb34..c2f1138cc9f 100644
--- a/src/torchmetrics/classification/jaccard.py
+++ b/src/torchmetrics/classification/jaccard.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -442,7 +442,7 @@ class JaccardIndex(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["JaccardIndex"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/matthews_corrcoef.py b/src/torchmetrics/classification/matthews_corrcoef.py
index cc86ccfc9bb..8fab20badf5 100644
--- a/src/torchmetrics/classification/matthews_corrcoef.py
+++ b/src/torchmetrics/classification/matthews_corrcoef.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -390,7 +390,7 @@ class MatthewsCorrCoef(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["MatthewsCorrCoef"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/precision_fixed_recall.py b/src/torchmetrics/classification/precision_fixed_recall.py
index ebaed8896fd..18536c6a0c2 100644
--- a/src/torchmetrics/classification/precision_fixed_recall.py
+++ b/src/torchmetrics/classification/precision_fixed_recall.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Tuple, Union
+from typing import Any, List, Optional, Sequence, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -482,7 +482,7 @@ class PrecisionAtFixedRecall(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["PrecisionAtFixedRecall"],
         task: Literal["binary", "multiclass", "multilabel"],
         min_recall: float,
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
diff --git a/src/torchmetrics/classification/precision_recall.py b/src/torchmetrics/classification/precision_recall.py
index d221584c336..9b658e8dac7 100644
--- a/src/torchmetrics/classification/precision_recall.py
+++ b/src/torchmetrics/classification/precision_recall.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -925,7 +925,7 @@ class Precision(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["Precision"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
@@ -988,7 +988,7 @@ class Recall(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["Recall"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/precision_recall_curve.py b/src/torchmetrics/classification/precision_recall_curve.py
index 9996cfd683e..c9e42d41b71 100644
--- a/src/torchmetrics/classification/precision_recall_curve.py
+++ b/src/torchmetrics/classification/precision_recall_curve.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Type, Union
 
 import torch
 from torch import Tensor
@@ -650,7 +650,7 @@ class PrecisionRecallCurve(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["PrecisionRecallCurve"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/recall_fixed_precision.py b/src/torchmetrics/classification/recall_fixed_precision.py
index bfbf5d68cd9..c9936f09411 100644
--- a/src/torchmetrics/classification/recall_fixed_precision.py
+++ b/src/torchmetrics/classification/recall_fixed_precision.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Sequence, Tuple, Union
+from typing import Any, List, Optional, Sequence, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -481,7 +481,7 @@ class RecallAtFixedPrecision(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["RecallAtFixedPrecision"],
         task: Literal["binary", "multiclass", "multilabel"],
         min_precision: float,
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
diff --git a/src/torchmetrics/classification/roc.py b/src/torchmetrics/classification/roc.py
index a391cd2046f..69400953d6d 100644
--- a/src/torchmetrics/classification/roc.py
+++ b/src/torchmetrics/classification/roc.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -559,7 +559,7 @@ class ROC(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["ROC"],
         task: Literal["binary", "multiclass", "multilabel"],
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/specificity.py b/src/torchmetrics/classification/specificity.py
index d9124968cfc..ec7a56b0fc7 100644
--- a/src/torchmetrics/classification/specificity.py
+++ b/src/torchmetrics/classification/specificity.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Optional, Sequence, Union
+from typing import Any, Optional, Sequence, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -474,7 +474,7 @@ class Specificity(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["Specificity"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/classification/specificity_sensitivity.py b/src/torchmetrics/classification/specificity_sensitivity.py
index c199f4dc7ad..bf4ba1a06b5 100644
--- a/src/torchmetrics/classification/specificity_sensitivity.py
+++ b/src/torchmetrics/classification/specificity_sensitivity.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, List, Optional, Tuple, Union
+from typing import Any, List, Optional, Tuple, Type, Union
 
 from torch import Tensor
 from typing_extensions import Literal
@@ -343,7 +343,7 @@ class SpecificityAtSensitivity(_ClassificationTaskWrapper):
     """
 
     def __new__(  # type: ignore[misc]
-        cls,
+        cls: Type["SpecificityAtSensitivity"],
         task: Literal["binary", "multiclass", "multilabel"],
         min_sensitivity: float,
         thresholds: Optional[Union[int, List[float], Tensor]] = None,
diff --git a/src/torchmetrics/classification/stat_scores.py b/src/torchmetrics/classification/stat_scores.py
index ce671e202bf..021c8582d30 100644
--- a/src/torchmetrics/classification/stat_scores.py
+++ b/src/torchmetrics/classification/stat_scores.py
@@ -11,7 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from typing import Any, Callable, List, Optional, Tuple, Union
+from typing import Any, Callable, List, Optional, Tuple, Type, Union
 
 import torch
 from torch import Tensor
@@ -513,7 +513,7 @@ class StatScores(_ClassificationTaskWrapper):
     """
 
     def __new__(
-        cls,
+        cls: Type["StatScores"],
         task: Literal["binary", "multiclass", "multilabel"],
         threshold: float = 0.5,
         num_classes: Optional[int] = None,
diff --git a/src/torchmetrics/functional/text/sacre_bleu.py b/src/torchmetrics/functional/text/sacre_bleu.py
index 69e2ae882f3..33c3afb0beb 100644
--- a/src/torchmetrics/functional/text/sacre_bleu.py
+++ b/src/torchmetrics/functional/text/sacre_bleu.py
@@ -41,7 +41,7 @@
 import re
 import tempfile
 from functools import partial
-from typing import Any, ClassVar, Dict, Optional, Sequence
+from typing import Any, ClassVar, Dict, Optional, Sequence, Type
 
 import torch
 from torch import Tensor, tensor
@@ -58,7 +58,7 @@
 )
 
 AVAILABLE_TOKENIZERS = ("none", "13a", "zh", "intl", "char", "ja-mecab", "ko-mecab", "flores101", "flores200")
-_Tokenizers_list = Literal["none", "13a", "zh", "intl", "char", "ja-mecab", "ko-mecab", "flores101", "flores200"]
+_TokenizersLiteral = Literal["none", "13a", "zh", "intl", "char", "ja-mecab", "ko-mecab", "flores101", "flores200"]
 
 _UCODE_RANGES = (
     ("\u3400", "\u4db5"),  # CJK Unified Ideographs Extension A, release 3.0
@@ -143,7 +143,7 @@ class _SacreBLEUTokenizer:
     # Keep it as class variable to avoid initializing over and over again
     sentencepiece_processors: ClassVar[Dict[str, Optional[Any]]] = {"flores101": None, "flores200": None}
 
-    def __init__(self, tokenize: _Tokenizers_list, lowercase: bool = False) -> None:
+    def __init__(self, tokenize: _TokenizersLiteral, lowercase: bool = False) -> None:
         self._check_tokenizers_validity(tokenize)
 
         self.tokenize_fn = getattr(self, self._TOKENIZE_FN[tokenize])
@@ -154,7 +154,12 @@ def __call__(self, line: str) -> Sequence[str]:
         return self._lower(tokenized_line, self.lowercase).split()
 
     @classmethod
-    def tokenize(cls, line: str, tokenize: _Tokenizers_list, lowercase: bool = False) -> Sequence[str]:
+    def tokenize(
+        cls: Type["_SacreBLEUTokenizer"],
+        line: str,
+        tokenize: _TokenizersLiteral,
+        lowercase: bool = False,
+    ) -> Sequence[str]:
         cls._check_tokenizers_validity(tokenize)
 
         tokenize_fn = getattr(cls, cls._TOKENIZE_FN[tokenize])
@@ -162,7 +167,7 @@ def tokenize(cls, line: str, tokenize: _Tokenizers_list, lowercase: bool = False
         return cls._lower(tokenized_line, lowercase).split()
 
     @classmethod
-    def _tokenize_regex(cls, line: str) -> str:
+    def _tokenize_regex(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Post-processing tokenizer for `13a` and `zh` tokenizers.
 
         Args:
@@ -191,7 +196,7 @@ def _is_chinese_char(uchar: str) -> bool:
         return any(start <= uchar <= end for start, end in _UCODE_RANGES)
 
     @classmethod
-    def _tokenize_base(cls, line: str) -> str:
+    def _tokenize_base(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes an input line with the tokenizer.
 
         Args:
@@ -204,7 +209,7 @@ def _tokenize_base(cls, line: str) -> str:
         return line
 
     @classmethod
-    def _tokenize_13a(cls, line: str) -> str:
+    def _tokenize_13a(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes a line using a relatively minimal tokenization that is equivalent to mteval-v13a, used by WMT.
 
         Args:
@@ -228,7 +233,7 @@ def _tokenize_13a(cls, line: str) -> str:
         return cls._tokenize_regex(f" {line} ")
 
     @classmethod
-    def _tokenize_zh(cls, line: str) -> str:
+    def _tokenize_zh(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenization of Chinese text.
 
         This is done in two steps: separate each Chinese characters (by utf-8 encoding) and afterwards tokenize the
@@ -256,7 +261,7 @@ def _tokenize_zh(cls, line: str) -> str:
         return cls._tokenize_regex(line_in_chars)
 
     @classmethod
-    def _tokenize_international(cls, line: str) -> str:
+    def _tokenize_international(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         r"""Tokenizes a string following the official BLEU implementation.
 
         See github.com/moses-smt/mosesdecoder/blob/master/scripts/generic/mteval-v14.pl#L954-L983
@@ -289,7 +294,7 @@ def _tokenize_international(cls, line: str) -> str:
         return " ".join(line.split())
 
     @classmethod
-    def _tokenize_char(cls, line: str) -> str:
+    def _tokenize_char(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes all the characters in the input line.
 
         Args:
@@ -302,7 +307,7 @@ def _tokenize_char(cls, line: str) -> str:
         return " ".join(char for char in line)
 
     @classmethod
-    def _tokenize_ja_mecab(cls, line: str) -> str:
+    def _tokenize_ja_mecab(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes a Japanese string line using MeCab morphological analyzer.
 
         Args:
@@ -321,7 +326,7 @@ def _tokenize_ja_mecab(cls, line: str) -> str:
         return tagger.parse(line).strip()
 
     @classmethod
-    def _tokenize_ko_mecab(cls, line: str) -> str:
+    def _tokenize_ko_mecab(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes a Korean string line using MeCab-korean morphological analyzer.
 
         Args:
@@ -340,7 +345,9 @@ def _tokenize_ko_mecab(cls, line: str) -> str:
         return tagger.parse(line).strip()
 
     @classmethod
-    def _tokenize_flores(cls, line: str, tokenize: Literal["flores101", "flores200"]) -> str:
+    def _tokenize_flores(
+        cls: Type["_SacreBLEUTokenizer"], line: str, tokenize: Literal["flores101", "flores200"]
+    ) -> str:
         """Tokenizes a string line using sentencepiece tokenizer.
 
         Args:
@@ -365,7 +372,7 @@ def _tokenize_flores(cls, line: str, tokenize: Literal["flores101", "flores200"]
         return " ".join(cls.sentencepiece_processors[tokenize].EncodeAsPieces(line))  # type: ignore[union-attr]
 
     @classmethod
-    def _tokenize_flores_101(cls, line: str) -> str:
+    def _tokenize_flores_101(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes a string line using sentencepiece tokenizer according to `FLORES-101`_ dataset.
 
         Args:
@@ -378,7 +385,7 @@ def _tokenize_flores_101(cls, line: str) -> str:
         return cls._tokenize_flores(line, "flores101")
 
     @classmethod
-    def _tokenize_flores_200(cls, line: str) -> str:
+    def _tokenize_flores_200(cls: Type["_SacreBLEUTokenizer"], line: str) -> str:
         """Tokenizes a string line using sentencepiece tokenizer according to `FLORES-200`_ dataset.
 
         Args:
@@ -397,7 +404,7 @@ def _lower(line: str, lowercase: bool) -> str:
         return line
 
     @classmethod
-    def _check_tokenizers_validity(cls, tokenize: _Tokenizers_list) -> None:
+    def _check_tokenizers_validity(cls: Type["_SacreBLEUTokenizer"], tokenize: _TokenizersLiteral) -> None:
         """Check if a supported tokenizer is chosen.
 
         Also check all dependencies of a given tokenizers are installed.
@@ -453,7 +460,7 @@ def sacre_bleu_score(
     target: Sequence[Sequence[str]],
     n_gram: int = 4,
     smooth: bool = False,
-    tokenize: _Tokenizers_list = "13a",
+    tokenize: _TokenizersLiteral = "13a",
     lowercase: bool = False,
     weights: Optional[Sequence[float]] = None,
 ) -> Tensor:
diff --git a/src/torchmetrics/functional/text/ter.py b/src/torchmetrics/functional/text/ter.py
index 4020f4e1d63..51d19120039 100644
--- a/src/torchmetrics/functional/text/ter.py
+++ b/src/torchmetrics/functional/text/ter.py
@@ -35,7 +35,7 @@
 
 import re
 from functools import lru_cache
-from typing import Dict, Iterator, List, Optional, Sequence, Tuple, Union
+from typing import Dict, Iterator, List, Optional, Sequence, Tuple, Type, Union
 
 from torch import Tensor, tensor
 
@@ -150,7 +150,7 @@ def _normalize_general_and_western(sentence: str) -> str:
         return sentence
 
     @classmethod
-    def _normalize_asian(cls, sentence: str) -> str:
+    def _normalize_asian(cls: Type["_TercomTokenizer"], sentence: str) -> str:
         """Split Chinese chars and Japanese kanji down to character level."""
         # 4E00—9FFF CJK Unified Ideographs
         # 3400—4DBF CJK Unified Ideographs Extension A
@@ -182,7 +182,7 @@ def _remove_punct(sentence: str) -> str:
         return re.sub(r"[\.,\?:;!\"\(\)]", "", sentence)
 
     @classmethod
-    def _remove_asian_punct(cls, sentence: str) -> str:
+    def _remove_asian_punct(cls: Type["_TercomTokenizer"], sentence: str) -> str:
         """Remove asian punctuation from an input sentence string."""
         sentence = re.sub(cls._ASIAN_PUNCTUATION, r"", sentence)
         return re.sub(cls._FULL_WIDTH_PUNCTUATION, r"", sentence)
diff --git a/src/torchmetrics/text/sacre_bleu.py b/src/torchmetrics/text/sacre_bleu.py
index 0708f51544f..8e2e63ad82b 100644
--- a/src/torchmetrics/text/sacre_bleu.py
+++ b/src/torchmetrics/text/sacre_bleu.py
@@ -22,7 +22,7 @@
 from torch import Tensor
 
 from torchmetrics.functional.text.bleu import _bleu_score_update
-from torchmetrics.functional.text.sacre_bleu import _SacreBLEUTokenizer, _Tokenizers_list
+from torchmetrics.functional.text.sacre_bleu import _SacreBLEUTokenizer, _TokenizersLiteral
 from torchmetrics.text.bleu import BLEUScore
 from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
@@ -91,7 +91,7 @@ def __init__(
         self,
         n_gram: int = 4,
         smooth: bool = False,
-        tokenize: _Tokenizers_list = "13a",
+        tokenize: _TokenizersLiteral = "13a",
         lowercase: bool = False,
         weights: Optional[Sequence[float]] = None,
         **kwargs: Any,
diff --git a/src/torchmetrics/utilities/enums.py b/src/torchmetrics/utilities/enums.py
index c5fce04c6c2..bfc2fd20190 100644
--- a/src/torchmetrics/utilities/enums.py
+++ b/src/torchmetrics/utilities/enums.py
@@ -11,6 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+from typing import Type
+
 from lightning_utilities.core.enums import StrEnum
 from typing_extensions import Literal
 
@@ -23,7 +25,7 @@ def _name() -> str:
         return "Task"
 
     @classmethod
-    def from_str(cls, value: str, source: Literal["key", "value", "any"] = "key") -> "EnumStr":
+    def from_str(cls: Type["EnumStr"], value: str, source: Literal["key", "value", "any"] = "key") -> "EnumStr":
         """Load from string.
 
         Raises:
diff --git a/tests/unittests/text/test_sacre_bleu.py b/tests/unittests/text/test_sacre_bleu.py
index 0fc6de59e11..c35603fa8b1 100644
--- a/tests/unittests/text/test_sacre_bleu.py
+++ b/tests/unittests/text/test_sacre_bleu.py
@@ -17,7 +17,7 @@
 
 import pytest
 from torch import Tensor, tensor
-from torchmetrics.functional.text.sacre_bleu import AVAILABLE_TOKENIZERS, _Tokenizers_list, sacre_bleu_score
+from torchmetrics.functional.text.sacre_bleu import AVAILABLE_TOKENIZERS, _TokenizersLiteral, sacre_bleu_score
 from torchmetrics.text.sacre_bleu import SacreBLEUScore
 from torchmetrics.utilities.imports import _SACREBLEU_AVAILABLE
 
@@ -128,4 +128,4 @@ def test_tokenize_ko_mecab():
 
 def test_equivalence_of_available_tokenizers_and_annotation():
     """Test equivalence of SacreBLEU available tokenizers and corresponding type annotation."""
-    assert set(AVAILABLE_TOKENIZERS) == set(_Tokenizers_list.__args__)
+    assert set(AVAILABLE_TOKENIZERS) == set(_TokenizersLiteral.__args__)