diff --git a/README.md b/README.md
index cb1b336b..afa2d504 100644
--- a/README.md
+++ b/README.md
@@ -36,7 +36,7 @@ pip install torchgfn[scripts]
 To install the cutting edge version (from the `main` branch):
 
 ```bash
-git clone https://github.com/saleml/torchgfn.git
+git clone https://github.com/GFNOrg/torchgfn.git
 conda create -n gfn python=3.10
 conda activate gfn
 cd torchgfn
diff --git a/src/gfn/containers/replay_buffer.py b/src/gfn/containers/replay_buffer.py
index a5205249..47352b82 100644
--- a/src/gfn/containers/replay_buffer.py
+++ b/src/gfn/containers/replay_buffer.py
@@ -155,8 +155,8 @@ def _add_objs(self, training_objects: Transitions | Trajectories | tuple[States]
 
         # Add the terminating states to the buffer.
         if self.terminating_states is not None:
-            assert terminating_states is not None
-            self.terminating_states.extend(terminating_states)
+            assert self.terminating_states is not None
+            self.terminating_states.extend(self.terminating_states)
 
             # Sort terminating states by logreward as well.
             self.terminating_states = self.terminating_states[ix]
@@ -164,7 +164,6 @@ def _add_objs(self, training_objects: Transitions | Trajectories | tuple[States]
 
     def add(self, training_objects: Transitions | Trajectories | tuple[States]):
         """Adds a training object to the buffer."""
-        terminating_states = None
         if isinstance(training_objects, tuple):
             assert self.objects_type == "states" and self.terminating_states is not None
             training_objects, terminating_states = training_objects
diff --git a/src/gfn/env.py b/src/gfn/env.py
index c1569235..c6097243 100644
--- a/src/gfn/env.py
+++ b/src/gfn/env.py
@@ -271,7 +271,7 @@ def log_reward(self, final_states: States) -> TT["batch_shape", torch.float]:
     @property
     def log_partition(self) -> float:
         "Returns the logarithm of the partition function."
-        return NotImplementedError(
+        raise NotImplementedError(
             "The environment does not support enumeration of states"
         )
 
@@ -432,20 +432,20 @@ def get_terminating_states_indices(
 
     @property
     def n_states(self) -> int:
-        return NotImplementedError(
+        raise NotImplementedError(
             "The environment does not support enumeration of states"
         )
 
     @property
     def n_terminating_states(self) -> int:
-        return NotImplementedError(
+        raise NotImplementedError(
             "The environment does not support enumeration of states"
         )
 
     @property
     def true_dist_pmf(self) -> TT["n_states", torch.float]:
         "Returns a one-dimensional tensor representing the true distribution."
-        return NotImplementedError(
+        raise NotImplementedError(
             "The environment does not support enumeration of states"
         )
 
@@ -456,7 +456,7 @@ def all_states(self) -> DiscreteStates:
         This should satisfy:
         self.get_states_indices(self.all_states) == torch.arange(self.n_states)
         """
-        return NotImplementedError(
+        raise NotImplementedError(
             "The environment does not support enumeration of states"
         )
 
@@ -467,6 +467,6 @@ def terminating_states(self) -> DiscreteStates:
         This should satisfy:
         self.get_terminating_states_indices(self.terminating_states) == torch.arange(self.n_terminating_states)
         """
-        return NotImplementedError(
+        raise NotImplementedError(
             "The environment does not support enumeration of states"
         )