diff --git a/data/tabular/mona/example_processing_and_templates.ipynb b/data/tabular/mona/example_processing_and_templates.ipynb
index 5f12a6f7f..786a90365 100644
--- a/data/tabular/mona/example_processing_and_templates.ipynb
+++ b/data/tabular/mona/example_processing_and_templates.ipynb
@@ -20,7 +20,6 @@
     "from tqdm import tqdm\n",
     "\n",
     "# import datasets\n",
-    "import rdkit\n",
     "import rdkit.Chem as Chem\n",
     "import rdkit.RDLogger as RDLogger"
    ]
@@ -1444,7 +1443,7 @@
     "                k = md[\"name\"]\n",
     "                v = md.get(\"value\", np.nan)\n",
     "                df_row[\"md_\" + transform_key(k)] = v\n",
-    "                if not (v is np.nan):\n",
+    "                if v is not np.nan:\n",
     "                    md_keys.append(k)\n",
     "            md_key_counter.update(md_keys)\n",
     "            compounds = entry.get(\"compound\", [])\n",
diff --git a/data/tabular/orbnet_denali/develop_transform.ipynb b/data/tabular/orbnet_denali/develop_transform.ipynb
index 039c60f89..5e7f1dab6 100644
--- a/data/tabular/orbnet_denali/develop_transform.ipynb
+++ b/data/tabular/orbnet_denali/develop_transform.ipynb
@@ -25,11 +25,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pathlib import Path\n",
     "from rdkit import Chem\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import os\n",
     "import pandas as pd\n",
     "from glob import glob"
    ]
@@ -474,7 +470,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from rdkit.Chem import rdDetermineBonds\n",
     "from chemnlp.utils import xyz_to_mol"
    ]
   },
diff --git a/experiments/ablations/continued_pretrain.py b/experiments/ablations/continued_pretrain.py
index 730453b95..0d5fd0577 100644
--- a/experiments/ablations/continued_pretrain.py
+++ b/experiments/ablations/continued_pretrain.py
@@ -57,7 +57,13 @@ def load_model(
 
 
 def train(
-    model, tokenizer, dataset, run_name: str, batch_size: int = 64, max_seq_length=2048, eval_dataset=None
+    model,
+    tokenizer,
+    dataset,
+    run_name: str,
+    batch_size: int = 64,
+    max_seq_length=2048,
+    eval_dataset=None,
 ):
     wandb.init(project="chemnlp-ablations", name=run_name)
     trainer = UnslothTrainer(
@@ -83,8 +89,8 @@ def train(
             lr_scheduler_type="linear",
             seed=3407,
             output_dir=f"outputs_{run_name}",
-            eval_strategy = 'steps' if eval_dataset is not None else 'no',
-            eval_steps = 10_000 if eval_dataset is not None else None
+            eval_strategy="steps" if eval_dataset is not None else "no",
+            eval_steps=10_000 if eval_dataset is not None else None,
         ),
     )
 
@@ -138,9 +144,18 @@ def run(
     )
 
     dataset = create_dataset(tokenizer, data_files)
-    eval_dataset = create_dataset(tokenizer, eval_data_files) if eval_data_files else None
+    eval_dataset = (
+        create_dataset(tokenizer, eval_data_files) if eval_data_files else None
+    )
 
-    train(model, tokenizer, dataset, run_name, batch_size=batch_size, eval_dataset=eval_dataset)
+    train(
+        model,
+        tokenizer,
+        dataset,
+        run_name,
+        batch_size=batch_size,
+        eval_dataset=eval_dataset,
+    )
 
 
 if __name__ == "__main__":
diff --git a/experiments/configs/data_configs/hf_data.yml b/experiments/configs/data_configs/hf_data.yml
index c3fec721e..64d71ab4e 100644
--- a/experiments/configs/data_configs/hf_data.yml
+++ b/experiments/configs/data_configs/hf_data.yml
@@ -1,7 +1,7 @@
 model_name: "EleutherAI/pythia-1b"
 context_length: 2048
 dataset_name: "EleutherAI/pile"
-dataset_args: {"name": "pubmed", "split": "train"}
+dataset_args: { "name": "pubmed", "split": "train" }
 batch_size: 1
 string_key: "text"
 save_path: "/fsx/proj-chemnlp/data/example_tokenised"