diff --git a/trains/binding/frameworks/__init__.py b/trains/binding/frameworks/__init__.py
index de2c347b..8b36ef9c 100644
--- a/trains/binding/frameworks/__init__.py
+++ b/trains/binding/frameworks/__init__.py
@@ -3,15 +3,20 @@ import shutil
 import sys
 import threading
 import weakref
+from random import randint
 from tempfile import mkstemp
+from typing import TYPE_CHECKING, Callable, Union
 
 import six
 from pathlib2 import Path
 
-from ...debugging.log import get_logger
-from ...config import running_remotely
-from ...model import InputModel, OutputModel
 from ...backend_interface.model import Model
+from ...config import running_remotely
+from ...debugging.log import get_logger
+from ...model import InputModel, OutputModel
+
+if TYPE_CHECKING:
+    from ...task import Task
 
 TrainsFrameworkAdapter = 'frameworks'
 _recursion_guard = {}
@@ -47,12 +52,60 @@ class WeightsFileHandler(object):
     _model_out_store_lookup = {}
     _model_in_store_lookup = {}
     _model_store_lookup_lock = threading.Lock()
+    _model_pre_callbacks = {}
+    _model_post_callbacks = {}
+
+    @staticmethod
+    def add_pre_callback(callback_function):
+        # type: (Callable[[Union['load', 'save'], str, str, Task], str]) -> int
+        if callback_function in WeightsFileHandler._model_pre_callbacks.values():
+            return [k for k, v in WeightsFileHandler._model_pre_callbacks.items() if v == callback_function][0]
+
+        while True:
+            h = randint(0, 1 << 31)
+            if h not in WeightsFileHandler._model_pre_callbacks:
+                break
+        WeightsFileHandler._model_pre_callbacks[h] = callback_function
+        return h
+
+    @staticmethod
+    def add_post_callback(callback_function):
+        # type: (Callable[[Union['load', 'save'], Model, str, str, str, Task], Model]) -> int
+        if callback_function in WeightsFileHandler._model_post_callbacks.values():
+            return [k for k, v in WeightsFileHandler._model_post_callbacks.items() if v == callback_function][0]
+
+        while True:
+            h = randint(0, 1 << 31)
+            if h not in WeightsFileHandler._model_post_callbacks:
+                break
+        WeightsFileHandler._model_post_callbacks[h] = callback_function
+        return h
+
+    @staticmethod
+    def remove_pre_callback(handle):
+        # type: (int) -> bool
+        if handle in WeightsFileHandler._model_pre_callbacks:
+            WeightsFileHandler._model_pre_callbacks.pop(handle, None)
+            return True
+        return False
+
+    @staticmethod
+    def remove_post_callback(handle):
+        # type: (int) -> bool
+        if handle in WeightsFileHandler._model_post_callbacks:
+            WeightsFileHandler._model_post_callbacks.pop(handle, None)
+            return True
+        return False
 
     @staticmethod
     def restore_weights_file(model, filepath, framework, task):
         if task is None:
             return filepath
 
+        # call pre model callback functions
+        for cb in WeightsFileHandler._model_pre_callbacks.values():
+            filepath = cb('load', filepath, framework, task)
+
         if not filepath:
             get_logger(TrainsFrameworkAdapter).debug("Could not retrieve model file location, model is not logged")
             return filepath
@@ -102,6 +155,10 @@ class WeightsFileHandler(object):
                     create_as_published=False,
                 )
 
+            # call post model callback functions
+            for cb in WeightsFileHandler._model_post_callbacks.values():
+                trains_in_model = cb('load', trains_in_model, filepath, filepath, framework, task)
+
             # noinspection PyBroadException
             try:
                 ref_model = weakref.ref(model)
@@ -167,7 +224,11 @@ class WeightsFileHandler(object):
                 except Exception:
                     pass
             else:
-                target_filename = files[0]
+                target_filename = Path(files[0]).name
+
+            # call pre model callback functions
+            for cb in WeightsFileHandler._model_pre_callbacks.values():
+                target_filename = cb('save', target_filename, framework, task)
 
             # check if object already has InputModel
             if trains_out_model is None:
@@ -191,7 +252,9 @@ class WeightsFileHandler(object):
                     # config_dict=config,
                     name=(task.name + ' - ' + model_name) if model_name else None,
                     label_enumeration=task.get_labels_enumeration(),
-                    framework=framework, base_model_id=in_model_id)
+                    framework=framework,
+                    base_model_id=in_model_id
+                )
                 # noinspection PyBroadException
                 try:
                     ref_model = weakref.ref(model)
@@ -199,23 +262,27 @@ class WeightsFileHandler(object):
                     ref_model = None
                 WeightsFileHandler._model_out_store_lookup[id(model)] = (trains_out_model, ref_model)
 
+            # call post model callback functions
+            for cb in WeightsFileHandler._model_post_callbacks.values():
+                trains_out_model = cb('save', trains_out_model, target_filename, saved_path, framework, task)
+
             # upload files if we found them, or just register the original path
             if trains_out_model.upload_storage_uri:
                 if len(files) > 1:
-                    trains_out_model.update_weights_package(weights_filenames=files, auto_delete_file=False,
-                                                            target_filename=target_filename)
+                    trains_out_model.update_weights_package(
+                        weights_filenames=files, auto_delete_file=False, target_filename=target_filename)
                 else:
                     # create a copy of the stored file,
                     # protect against someone deletes/renames the file before async upload finish is done
-                    target_filename = Path(files[0]).name
+
                     # HACK: if pytorch-lightning is used, remove the temp '.part' file extension
                     if sys.modules.get('pytorch_lightning') and target_filename.lower().endswith('.part'):
                         target_filename = target_filename[:-len('.part')]
                     fd, temp_file = mkstemp(prefix='.trains.upload_model_', suffix='.tmp')
                     os.close(fd)
                     shutil.copy(files[0], temp_file)
-                    trains_out_model.update_weights(weights_filename=temp_file, auto_delete_file=True,
-                                                    target_filename=target_filename)
+                    trains_out_model.update_weights(
+                        weights_filename=temp_file, auto_delete_file=True, target_filename=target_filename)
             else:
                 trains_out_model.update_weights(weights_filename=None, register_uri=saved_path)
         except Exception as ex: