diff --git a/docs/conf.py b/docs/conf.py
index 8a5371f..6e7a9d5 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -49,7 +49,7 @@
 # The short X.Y version
 version = '0.13'
 # The full version, including alpha/beta/rc tags
-release = '0.13.6'
+release = '0.13.7'
 
 # -- General configuration ---------------------------------------------------
 
diff --git a/docs/examples/monitor_fastai.ipynb b/docs/examples/monitor_fastai.ipynb
index 355830b..1a96544 100644
--- a/docs/examples/monitor_fastai.ipynb
+++ b/docs/examples/monitor_fastai.ipynb
@@ -19,14 +19,10 @@
    "outputs": [],
    "source": [
     "from fastai.vision import *\n",
-    "mnist = untar_data(URLs.MNIST_TINY)\n",
-    "tfms = get_transforms(do_flip=False)\n",
-    "data = (ImageItemList.from_folder(mnist)\n",
-    "    .split_by_folder()\n",
-    "    .label_from_folder()\n",
-    "    .transform(tfms, size=32)\n",
-    "    .databunch()\n",
-    "    .normalize(imagenet_stats))"
+    "path = untar_data(URLs.MNIST_TINY)\n",
+    "\n",
+    "data = ImageDataBunch.from_folder(path, ds_tfms=(rand_pad(2, 28), []), bs=64)\n",
+    "data.normalize(imagenet_stats)"
    ]
   },
   {
@@ -42,7 +38,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "learn = create_cnn(data, models.resnet18, metrics=accuracy)\n",
+    "learn = cnn_learner(data, models.resnet18, metrics=accuracy)\n",
     "learn.lr_find()\n",
     "learn.recorder.plot()"
    ]
diff --git a/neptunecontrib/monitoring/fastai.py b/neptunecontrib/monitoring/fastai.py
index 2c01a5e..ef68bb7 100644
--- a/neptunecontrib/monitoring/fastai.py
+++ b/neptunecontrib/monitoring/fastai.py
@@ -48,14 +48,15 @@ class NeptuneMonitor(LearnerCallback):
         Prepare data::
 
             from fastai.vision import *
-            mnist = untar_data(URLs.MNIST_TINY)
-            tfms = get_transforms(do_flip=False)
-            data = (ImageItemList.from_folder(mnist)
-                          .split_by_folder()
-                          .label_from_folder()
-                          .transform(tfms, size=32)
-                          .databunch()
-                          .normalize(imagenet_stats))
+            path = untar_data(URLs.MNIST_TINY)
+
+            data = ImageDataBunch.from_folder(path, ds_tfms=(rand_pad(2, 28), []), bs=64)
+            data.normalize(imagenet_stats)
+
+            learn = cnn_learner(data, models.resnet18, metrics=accuracy)
+
+            learn.lr_find()
+            learn.recorder.plot()
 
         Now, create Neptune experiment, instantiate the monitor and pass
         it to callbacks::
diff --git a/setup.py b/setup.py
index 1aa6826..f72fbb4 100644
--- a/setup.py
+++ b/setup.py
@@ -20,7 +20,7 @@ def main():
 
     setup(
         name='neptune-contrib',
-        version='0.13.6',
+        version='0.13.7',
         description='Neptune Python library contributions',
         author='neptune.ml',
         author_email='contact@neptune.ml',