diff --git a/src/refiners/training_utils/trainer.py b/src/refiners/training_utils/trainer.py
index 730bb8a..40cad58 100644
--- a/src/refiners/training_utils/trainer.py
+++ b/src/refiners/training_utils/trainer.py
@@ -1,5 +1,6 @@
 import random
 import time
+from abc import ABC, abstractmethod
 from functools import cached_property, wraps
 from pathlib import Path
 from typing import Any, Callable, Generic, Iterable, TypeVar, cast
@@ -264,7 +265,7 @@ Batch = TypeVar("Batch")
 ConfigType = TypeVar("ConfigType", bound=BaseConfig)
 
 
-class Trainer(Generic[ConfigType, Batch]):
+class Trainer(Generic[ConfigType, Batch], ABC):
     def __init__(self, config: ConfigType, callbacks: list[Callback[Any]] | None = None) -> None:
         self.config = config
         self.clock = TrainingClock(
@@ -440,11 +441,13 @@ class Trainer(Generic[ConfigType, Batch]):
             self.checkpoints_save_folder = None
             logger.info("Checkpointing disabled: configure `save_folder` to turn it on.")
 
+    @abstractmethod
     def load_models(self) -> dict[str, fl.Module]:
-        raise NotImplementedError("The `load_models` method must be implemented in the subclass.")
+        ...
 
+    @abstractmethod
     def load_dataset(self) -> Dataset[Batch]:
-        raise NotImplementedError("The `load_dataset` method must be implemented in the subclass.")
+        ...
 
     @cached_property
     def dataset(self) -> Dataset[Batch]:
@@ -471,8 +474,9 @@ class Trainer(Generic[ConfigType, Batch]):
         assert self.checkpoints_save_folder is not None
         return self.checkpoints_save_folder
 
+    @abstractmethod
     def compute_loss(self, batch: Batch) -> Tensor:
-        raise NotImplementedError("The `compute_loss` method must be implemented in the subclass.")
+        ...
 
     def compute_evaluation(self) -> None:
         pass