diff --git a/notebooks/downstream_adaptation.ipynb b/notebooks/downstream_adaptation.ipynb
index c2fc509..8ea5431 100644
--- a/notebooks/downstream_adaptation.ipynb
+++ b/notebooks/downstream_adaptation.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "This example shows how MiniMol can featurise small molecules that will then serve as an input to another model trained on a small downstream dataset from TDC ADMET. This allows to transfer the knowledge from the pre-trained MiniMol to another task. \n",
     "\n",
-    "Before we start, let's make sure that the TDC package is installed in the environment. It takes a while, that's why we don't include it in the dependencies."
+    "Before we start, let's make sure that the TDC package is installed in the environment. The package is quite large, and we assume that a user wouldn't necesserily need it in their work, that's why we don't include it in the dependencies."
    ]
   },
   {
@@ -17,7 +17,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# %pip install PyTDC"
+    "%pip install PyTDC"
    ]
   },
   {
@@ -540,7 +540,7 @@
     "\n",
     "- Rather than choosing the model at the last epoch, we will use best validation loss to decide which one to choose.\n",
     "\n",
-    "Below we implement a method that create a new training and validation dataloader for each fold, and also a method for ensemble-based evaluationm, where probabiltiies for each predition are averaged across all models in the ensemble."
+    "We already implemented a `dataloader_factory()` method that creates a new training and validation dataloader for each fold. Now, we will also build a method for ensemble-based evaluation, that takes a list of models and where probabiltiies for each sample from all of them are averaged, creating an ensemble. "
    ]
   },
   {
diff --git a/setup.py b/setup.py
index f1d4738..1a3058b 100644
--- a/setup.py
+++ b/setup.py
@@ -6,7 +6,7 @@
 
 setup(
     name='minimol',
-    version='1.1',
+    version='1.2',
     packages=find_packages(),
     include_package_data=True,
     package_data={