diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
index 23f0a095ea..61eb6bfb3c 100644
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -15,7 +15,7 @@ jobs:
 
       - uses: actions/setup-python@v4
         with:
-          python-version: "3.9"
+          python-version: "3.10"
           cache: "pip"
 
       - name: Install dependencies
diff --git a/mteb/abstasks/AbsTaskClassification.py b/mteb/abstasks/AbsTaskClassification.py
index eac41856e8..b47c8d68c0 100644
--- a/mteb/abstasks/AbsTaskClassification.py
+++ b/mteb/abstasks/AbsTaskClassification.py
@@ -150,7 +150,7 @@ def _evaluate_subset(
         )  # we store idxs to make the shuffling reproducible
         for i in range(self.n_experiments):
             logger.info(
-                "=" * 10 + f" Experiment {i+1}/{self.n_experiments} " + "=" * 10
+                "=" * 10 + f" Experiment {i + 1}/{self.n_experiments} " + "=" * 10
             )
             # Bootstrap `self.samples_per_label` samples per label for each split
             X_sampled, y_sampled, idxs = self._undersample_data(
diff --git a/mteb/abstasks/AbsTaskMultilabelClassification.py b/mteb/abstasks/AbsTaskMultilabelClassification.py
index cbcb125021..f9052c8b47 100644
--- a/mteb/abstasks/AbsTaskMultilabelClassification.py
+++ b/mteb/abstasks/AbsTaskMultilabelClassification.py
@@ -215,7 +215,7 @@ def _evaluate_subset(
         for i_experiment, sample_indices in enumerate(train_samples):
             logger.info(
                 "=" * 10
-                + f" Experiment {i_experiment+1}/{self.n_experiments} "
+                + f" Experiment {i_experiment + 1}/{self.n_experiments} "
                 + "=" * 10
             )
             X_train = np.stack([unique_train_embeddings[idx] for idx in sample_indices])
diff --git a/mteb/abstasks/AbsTaskSpeedTask.py b/mteb/abstasks/AbsTaskSpeedTask.py
index 7a73da445b..0d3f8ae8dd 100644
--- a/mteb/abstasks/AbsTaskSpeedTask.py
+++ b/mteb/abstasks/AbsTaskSpeedTask.py
@@ -78,7 +78,7 @@ def get_system_info(self) -> dict[str, str]:
                 list_gpus.append(
                     {
                         "gpu_name": gpu.name,
-                        "gpu_total_memory": f"{gpu.memoryTotal/1024.0} GB",
+                        "gpu_total_memory": f"{gpu.memoryTotal / 1024.0} GB",
                     }
                 )
             info["gpu_info"] = list_gpus
diff --git a/mteb/abstasks/Image/AbsTaskImageClassification.py b/mteb/abstasks/Image/AbsTaskImageClassification.py
index 7add58296a..c7afbe1136 100644
--- a/mteb/abstasks/Image/AbsTaskImageClassification.py
+++ b/mteb/abstasks/Image/AbsTaskImageClassification.py
@@ -133,7 +133,7 @@ def _evaluate_subset(
         )  # we store idxs to make the shuffling reproducible
         for i in range(self.n_experiments):
             logger.info(
-                "=" * 10 + f" Experiment {i+1}/{self.n_experiments} " + "=" * 10
+                "=" * 10 + f" Experiment {i + 1}/{self.n_experiments} " + "=" * 10
             )
             # Bootstrap `self.samples_per_label` samples per label for each split
             undersampled_train, idxs = self._undersample_data(
diff --git a/mteb/abstasks/Image/AbsTaskImageMultilabelClassification.py b/mteb/abstasks/Image/AbsTaskImageMultilabelClassification.py
index dc779d5e69..26fd799d56 100644
--- a/mteb/abstasks/Image/AbsTaskImageMultilabelClassification.py
+++ b/mteb/abstasks/Image/AbsTaskImageMultilabelClassification.py
@@ -183,7 +183,7 @@ def _evaluate_subset(
         for i_experiment, sample_indices in enumerate(train_samples):
             logger.info(
                 "=" * 10
-                + f" Experiment {i_experiment+1}/{self.n_experiments} "
+                + f" Experiment {i_experiment + 1}/{self.n_experiments} "
                 + "=" * 10
             )
             X_train = np.stack([unique_train_embeddings[idx] for idx in sample_indices])
diff --git a/mteb/tasks/Retrieval/eng/LitSearchRetrieval.py b/mteb/tasks/Retrieval/eng/LitSearchRetrieval.py
index 2c823e85dd..b9c3683ed4 100644
--- a/mteb/tasks/Retrieval/eng/LitSearchRetrieval.py
+++ b/mteb/tasks/Retrieval/eng/LitSearchRetrieval.py
@@ -52,7 +52,7 @@ def load_data(self, **kwargs):
 
         self.queries["test"] = dict(
             zip(
-                [f"q{x+1}" for x in range(len(query_ds["full"]))],
+                [f"q{x + 1}" for x in range(len(query_ds["full"]))],
                 query_ds["full"]["query"],
             )
         )
@@ -69,7 +69,7 @@ def load_data(self, **kwargs):
         }
 
         self.relevant_docs["test"] = {
-            f"q{e+1}": dict(zip([f"d{i}" for i in ids], range(1, len(ids) + 1)))
+            f"q{e + 1}": dict(zip([f"d{i}" for i in ids], range(1, len(ids) + 1)))
             for e, ids in enumerate(query_ds["full"]["corpusids"])
         }
 
diff --git a/mteb/tasks/Retrieval/slk/SlovakSumRetrieval.py b/mteb/tasks/Retrieval/slk/SlovakSumRetrieval.py
index 0b26fd1079..ea08c03225 100644
--- a/mteb/tasks/Retrieval/slk/SlovakSumRetrieval.py
+++ b/mteb/tasks/Retrieval/slk/SlovakSumRetrieval.py
@@ -56,12 +56,12 @@ def load_data(self, **kwargs):
                 dataset_path, split=f"{split}[:{n_sample}]"
             )
             # Transforming news summary into retrieval task
-            queries = {f"q{e+1}": x["sum"] for e, x in enumerate(split_ds)}
+            queries = {f"q{e + 1}": x["sum"] for e, x in enumerate(split_ds)}
             corpus = {
-                f"d{e+1}": {"title": x["title"], "text": x["text"]}
+                f"d{e + 1}": {"title": x["title"], "text": x["text"]}
                 for e, x in enumerate(split_ds)
             }
-            qrels = {f"q{i+1}": {f"d{i+1}": 1} for i in range(split_ds.shape[0])}
+            qrels = {f"q{i + 1}": {f"d{i + 1}": 1} for i in range(split_ds.shape[0])}
             self.corpus[split], self.queries[split], self.relevant_docs[split] = (
                 corpus,
                 queries,
diff --git a/scripts/task_selection/task_selection_eng_lite.ipynb b/scripts/task_selection/task_selection_eng_lite.ipynb
index ec81fe2893..49e4fba565 100644
--- a/scripts/task_selection/task_selection_eng_lite.ipynb
+++ b/scripts/task_selection/task_selection_eng_lite.ipynb
@@ -2551,7 +2551,7 @@
     "for model, revision in mteb_results.items():\n",
     "    for rev, results in revision.items():\n",
     "        print(\n",
-    "            f\"{model}: {sum(res.evaluation_time for res in results) / 3600    :.2f} hours\"\n",
+    "            f\"{model}: {sum(res.evaluation_time for res in results) / 3600:.2f} hours\"\n",
     "        )"
    ]
   },