diff --git a/learner_gp.py b/learner_gp.py
index 5124917..50dbba6 100644
--- a/learner_gp.py
+++ b/learner_gp.py
@@ -52,10 +52,10 @@
         ent_coef=0.01,
     )
 
-    run_id = "gp_run3.51"
+    run_id = "gp_run3.52"
     wandb.login(key=os.environ["WANDB_KEY"])
     logger = wandb.init(dir="./wandb_store",
-                        name="GP_Run3.51",
+                        name="GP_Run3.52",
                         project="Opti",
                         entity="kaiyotech",
                         id=run_id,
@@ -154,7 +154,7 @@
         disable_gradient_logging=True,
     )
 
-    alg.load("GP_saves/Opti_1682617673.747051/Opti_40310/checkpoint.pt")
+    alg.load("GP_saves/Opti_1682795258.7251265/Opti_41230/checkpoint.pt")
     
 
     alg.agent.optimizer.param_groups[0]["lr"] = logger.config.actor_lr
diff --git a/pretrained_agents/nexto/nexto_v2.py b/pretrained_agents/nexto/nexto_v2.py
index 7d0b0de..45e5bcf 100644
--- a/pretrained_agents/nexto/nexto_v2.py
+++ b/pretrained_agents/nexto/nexto_v2.py
@@ -14,11 +14,12 @@
 
 
 class NextoV2(HardcodedAgent):
-    def __init__(self, model_string, n_players):
+    def __init__(self, model_string, n_players, tick_skip_skip=2):
         cur_dir = os.path.dirname(os.path.realpath(__file__))
         self.actor = torch.jit.load(os.path.join(cur_dir, model_string))
         self.obs_builder = Nexto_V2_ObsBuilder(n_players=n_players)
         self.previous_action = np.array([0, 0, 0, 0, 0, 0, 0, 0])
+        self.tick_skip_skip = tick_skip_skip
 
         self._lookup_table = self.make_lookup_table()