diff --git a/official/vision/beta/configs/image_classification.py b/official/vision/beta/configs/image_classification.py
index 870e82979fc1d28596b244ba0a1ed0c828b6898c..d88f30667ee5aa106ae0c2bf7a86040f3e7feb86 100644
--- a/official/vision/beta/configs/image_classification.py
+++ b/official/vision/beta/configs/image_classification.py
@@ -15,7 +15,7 @@
 # ==============================================================================
 """Image classification configuration definition."""
 import os
-from typing import List
+from typing import List, Optional
 import dataclasses
 from official.core import config_definitions as cfg
 from official.core import exp_factory
@@ -63,6 +63,8 @@ class ImageClassificationTask(cfg.TaskConfig):
   validation_data: DataConfig = DataConfig(is_training=False)
   losses: Losses = Losses()
   gradient_clip_norm: float = 0.0
+  init_checkpoint: Optional[str] = None
+  init_checkpoint_modules: str = 'all'  # all or backbone
 
 
 @exp_factory.register_config_factory('image_classification')
diff --git a/official/vision/beta/tasks/image_classification.py b/official/vision/beta/tasks/image_classification.py
index ab93d3b67f4c45061ca9711ba629618686fa9d38..d34b4902ba60cfbc78f6b9519f7bb3aa069bdab8 100644
--- a/official/vision/beta/tasks/image_classification.py
+++ b/official/vision/beta/tasks/image_classification.py
@@ -14,6 +14,7 @@
 # limitations under the License.
 # ==============================================================================
 """Image classification task definition."""
+from absl import logging
 import tensorflow as tf
 from official.core import base_task
 from official.core import input_reader
@@ -46,6 +47,30 @@ class ImageClassificationTask(base_task.Task):
         l2_regularizer=l2_regularizer)
     return model
 
+  def initialize(self, model: tf.keras.Model):
+    """Loading pretrained checkpoint."""
+    if not self.task_config.init_checkpoint:
+      return
+
+    ckpt_dir_or_file = self.task_config.init_checkpoint
+    if tf.io.gfile.isdir(ckpt_dir_or_file):
+      ckpt_dir_or_file = tf.train.latest_checkpoint(ckpt_dir_or_file)
+
+    # Restoring checkpoint.
+    if self.task_config.init_checkpoint_modules == 'all':
+      ckpt = tf.train.Checkpoint(**model.checkpoint_items)
+      status = ckpt.restore(ckpt_dir_or_file)
+      status.assert_consumed()
+    elif self.task_config.init_checkpoint_modules == 'backbone':
+      ckpt = tf.train.Checkpoint(backbone=model.backbone)
+      status = ckpt.restore(ckpt_dir_or_file)
+      status.expect_partial().assert_existing_objects_matched()
+    else:
+      assert "Only 'all' or 'backbone' can be used to initialize the model."
+
+    logging.info('Finished loading pretrained checkpoint from %s',
+                 ckpt_dir_or_file)
+
   def build_inputs(self, params, input_context=None):
     """Builds classification input."""