diff --git a/CHANGELOG.md b/CHANGELOG.md
index c6bb4f600..31e55d21d 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -7,9 +7,10 @@
 ### New Features
 - feature: Error information is printed to the console on failed runs and evaluations.
 - feature: The stack trace of a failed run/evaluation is included in the `FailedExampleRun`/`FailedExampleEvaluation` object
-- feature: The `Runner.run_dataset` and `Evaluator.evaluate_run` have an optional flag `abort_on_error` to stop running/evaluating when an error occurs.
-- feature: Added `Runner.failed_runs` and `Evaluator.failed_evaluations` to retrieve all failed run / evaluation lineages
-- feature: Added `.successful_example_outputs` and `.failed_example_outputs` to `RunRepository` to match the evaluation repository
+- feature: The `Runner.run_dataset(..)` and `Evaluator.evaluate_run(..)` have an optional flag `abort_on_error` to stop running/evaluating when an error occurs.
+- feature: Added `Runner.failed_runs(..)` and `Evaluator.failed_evaluations(..)` to retrieve all failed run / evaluation lineages
+- feature: Added `.successful_example_outputs(..)` and `.failed_example_outputs(..)` to `RunRepository` to match the evaluation repository
+- feature: Added optional argument to set an id when creating a `Dataset` via `DatasetRepository.create_dataset(..)`
 
 ### Fixes
 
diff --git a/src/intelligence_layer/evaluation/dataset/dataset_repository.py b/src/intelligence_layer/evaluation/dataset/dataset_repository.py
index a97301e3f..aecf89b24 100644
--- a/src/intelligence_layer/evaluation/dataset/dataset_repository.py
+++ b/src/intelligence_layer/evaluation/dataset/dataset_repository.py
@@ -17,13 +17,17 @@ class DatasetRepository(ABC):
 
     @abstractmethod
     def create_dataset(
-        self, examples: Iterable[Example[Input, ExpectedOutput]], dataset_name: str
+        self,
+        examples: Iterable[Example[Input, ExpectedOutput]],
+        dataset_name: str,
+        id: str | None = None,
     ) -> Dataset:
         """Creates a dataset from given :class:`Example`s and returns the ID of that dataset.
 
         Args:
             examples: An :class:`Iterable` of :class:`Example`s to be saved in the same dataset.
             dataset_name: A name for the dataset.
+            id: The dataset ID. If `None`, an ID will be generated.
 
         Returns:
             The created :class:`Dataset`.
diff --git a/src/intelligence_layer/evaluation/dataset/file_dataset_repository.py b/src/intelligence_layer/evaluation/dataset/file_dataset_repository.py
index 8708e5bf2..cbe2c4a80 100644
--- a/src/intelligence_layer/evaluation/dataset/file_dataset_repository.py
+++ b/src/intelligence_layer/evaluation/dataset/file_dataset_repository.py
@@ -28,10 +28,9 @@ def create_dataset(
         dataset_name: str,
         id: str | None = None,
     ) -> Dataset:
-        if id is None:
-            dataset = Dataset(name=dataset_name)
-        else:
-            dataset = Dataset(name=dataset_name, id=id)
+        dataset = Dataset(name=dataset_name)
+        if id is not None:
+            dataset.id = id
 
         self.mkdir(self._dataset_directory(dataset.id))
 
@@ -146,17 +145,11 @@ def _write_data(
         file_path: Path,
         data_to_write: Iterable[PydanticSerializable],
     ) -> None:
-        data = "\n".join(JsonSerializer(root=chunk).model_dump_json() for chunk in data_to_write)
+        data = "\n".join(
+            JsonSerializer(root=chunk).model_dump_json() for chunk in data_to_write
+        )
         self.write_utf8(file_path, data, create_parents=True)
 
-        # with self._file_system.open(
-        #     self.path_to_str(file_path), "w", encoding="utf-8"
-        # ) as file:
-        #     for data_chunk in data_to_write:
-        #         serialized_result = JsonSerializer(root=data_chunk)
-        #         json_string = serialized_result.model_dump_json() + "\n"
-        #         file.write(json_string)
-
 
 class FileDatasetRepository(FileSystemDatasetRepository):
     def __init__(self, root_directory: Path) -> None:
diff --git a/src/intelligence_layer/evaluation/dataset/hugging_face_dataset_repository.py b/src/intelligence_layer/evaluation/dataset/hugging_face_dataset_repository.py
index a1c11b346..604603c4e 100644
--- a/src/intelligence_layer/evaluation/dataset/hugging_face_dataset_repository.py
+++ b/src/intelligence_layer/evaluation/dataset/hugging_face_dataset_repository.py
@@ -1,18 +1,10 @@
-import time
 from pathlib import Path
-from typing import Iterable, Optional
-import typing
+from typing import Optional
 
 import huggingface_hub  # type: ignore
 from huggingface_hub import HfFileSystem, create_repo
-from huggingface_hub.utils import HfHubHTTPError
 
-from intelligence_layer.core.task import Input
-from intelligence_layer.evaluation.dataset.domain import (
-    Dataset,
-    Example,
-    ExpectedOutput,
-)
+from intelligence_layer.evaluation.dataset.domain import Dataset
 from intelligence_layer.evaluation.dataset.file_dataset_repository import (
     FileSystemDatasetRepository,
 )
@@ -50,25 +42,6 @@ def __init__(self, repository_id: str, token: str, private: bool) -> None:
         self._repository_id = repository_id
         self._file_system = file_system  # for better type checks
 
-    # def create_dataset(
-    #     self,
-    #     examples: Iterable[Example[Input, ExpectedOutput]],
-    #     dataset_name: str,
-    #     id: str | None = None,
-    # ) -> Dataset:
-    #     failures = 0
-    #     exception = None
-    #     while failures < 5:
-    #         try:
-    #             dataset = super().create_dataset(examples, dataset_name, id)
-    #             return dataset
-    #         except Exception as e:
-    #             exception = typing.cast(HfHubHTTPError, e)
-    #         failures += 1
-    #         print(f"Failure {failures}")
-    #         time.sleep(0.5)
-    #     raise exception  # RuntimeError("Cannot create dataset on Huggingface.")
-
     def delete_repository(self) -> None:
         huggingface_hub.delete_repo(
             repo_id=self._repository_id,
diff --git a/src/intelligence_layer/evaluation/dataset/in_memory_dataset_repository.py b/src/intelligence_layer/evaluation/dataset/in_memory_dataset_repository.py
index 36bc35931..4504b98a5 100644
--- a/src/intelligence_layer/evaluation/dataset/in_memory_dataset_repository.py
+++ b/src/intelligence_layer/evaluation/dataset/in_memory_dataset_repository.py
@@ -19,9 +19,14 @@ def __init__(self) -> None:
         ] = {}
 
     def create_dataset(
-        self, examples: Iterable[Example[Input, ExpectedOutput]], dataset_name: str
+        self,
+        examples: Iterable[Example[Input, ExpectedOutput]],
+        dataset_name: str,
+        id: str | None = None,
     ) -> Dataset:
         dataset = Dataset(name=dataset_name)
+        if id is not None:
+            dataset.id = id
         if dataset.id in self._datasets_and_examples:
             raise ValueError(
                 f"Created random dataset ID already exists for dataset {dataset}. This should not happen."
diff --git a/src/intelligence_layer/evaluation/dataset/single_huggingface_dataset_repository.py b/src/intelligence_layer/evaluation/dataset/single_huggingface_dataset_repository.py
index 184878f9a..6c25dccbe 100644
--- a/src/intelligence_layer/evaluation/dataset/single_huggingface_dataset_repository.py
+++ b/src/intelligence_layer/evaluation/dataset/single_huggingface_dataset_repository.py
@@ -28,7 +28,10 @@ def __init__(
         self._huggingface_dataset = huggingface_dataset
 
     def create_dataset(
-        self, examples: Iterable[Example[Input, ExpectedOutput]], dataset_name: str
+        self,
+        examples: Iterable[Example[Input, ExpectedOutput]],
+        dataset_name: str,
+        id: str | None = None,
     ) -> Dataset:
         raise NotImplementedError
 
diff --git a/tests/evaluation/test_dataset_repository.py b/tests/evaluation/test_dataset_repository.py
index cf6ea7c70..c1f202a57 100644
--- a/tests/evaluation/test_dataset_repository.py
+++ b/tests/evaluation/test_dataset_repository.py
@@ -24,6 +24,26 @@ def file_dataset_repository(tmp_path: Path) -> FileDatasetRepository:
 ]
 
 
+@mark.parametrize(
+    "repository_fixture",
+    test_repository_fixtures,
+)
+def test_dataset_repository_with_custom_id(
+    repository_fixture: str,
+    request: FixtureRequest,
+    dummy_string_example: Example[DummyStringInput, DummyStringOutput],
+) -> None:
+    dataset_repository: DatasetRepository = request.getfixturevalue(repository_fixture)
+
+    dataset = dataset_repository.create_dataset(
+        examples=[dummy_string_example],
+        dataset_name="test-dataset",
+        id="my-custom-dataset-id",
+    )
+
+    assert dataset.id == "my-custom-dataset-id"
+
+
 @mark.parametrize(
     "repository_fixture",
     test_repository_fixtures,