diff --git a/environment.yml b/environment.yml
index d883e016..657319f4 100644
--- a/environment.yml
+++ b/environment.yml
@@ -24,7 +24,7 @@ dependencies:
   - pydocstyle
   - toml
   - twine
-  - build
+  - python-build
   - pip
   - pip:
     - "--editable=.[dev]"
diff --git a/sleap_io/io/nwb.py b/sleap_io/io/nwb.py
index 4e922a52..68ad466f 100644
--- a/sleap_io/io/nwb.py
+++ b/sleap_io/io/nwb.py
@@ -24,7 +24,6 @@
 except ImportError:
     ArrayLike = np.ndarray
 
-from hdmf.utils import LabelledDict
 from hdmf.build.errors import OrphanContainerBuildError
 
 from pynwb import NWBFile, NWBHDF5IO, ProcessingModule
@@ -72,10 +71,7 @@ def pose_training_to_labels(pose_training: PoseTraining) -> Labels:  # type: ign
     training_frames = pose_training.training_frames.training_frames.values()
     for training_frame in training_frames:
         source_video = training_frame.source_video
-        if source_video.format == "external" and len(source_video.external_file) == 1:
-            video = Video(source_video.external_file[0])
-        else:
-            raise NotImplementedError("Only single-file external videos are supported.")
+        video = Video(source_video.external_file)
 
         frame_idx = training_frame.source_video_frame_index
         instances = []
@@ -89,7 +85,7 @@ def pose_training_to_labels(pose_training: PoseTraining) -> Labels:  # type: ign
                 Instance.from_numpy(
                     points=instance.node_locations[:], skeleton=skeleton
                 )
-            )  # `track` field is not stored in `SkeletonInstance` objects
+            )
         labeled_frames.append(
             LabeledFrame(video=video, frame_idx=frame_idx, instances=instances)
         )
@@ -212,8 +208,6 @@ def instance_to_skeleton_instance(
     return SkeletonInstance(
         name=f"skeleton_instance_{id(instance)}",
         id=np.uint64(id(instance)),
-        # TODO add a counter in the loop to track the number of instances
-        # instead of using id
         node_locations=np_node_locations,
         node_visibility=[point.visible for point in instance.points.values()],
         skeleton=skeleton,
@@ -620,7 +614,7 @@ def append_nwb_data(
             .unique()
         )
 
-        for track_index, track_name in enumerate(name_of_tracks_in_video):
+        for  track_name in name_of_tracks_in_video:
             pose_estimation_container = build_pose_estimation_container_for_track(
                 labels_data_df,
                 labels,
@@ -688,52 +682,11 @@ def append_nwb_training(
         pose_training = labels_to_pose_training(labels, skeletons_list, video_info)
         nwb_processing_module.add(pose_training)
 
-        confidence_definition = "Softmax output of the deep neural network"
-        reference_frame = (
-            "The coordinates are in (x, y) relative to the top-left of the image. "
-            "Coordinates refer to the midpoint of the pixel. "
-            "That is, t the midpoint of the top-left pixel is at (0, 0), whereas "
-            "the top-left corner of that same pixel is at (-0.5, -0.5)."
-        )
-        pose_estimation_series_list = []
-        for node in skeletons_list[0].nodes:
-            pose_estimation_series = PoseEstimationSeries(
-                name=node,
-                description=f"Marker placed on {node}",
-                data=np.random.rand(100, 2),
-                unit="pixels",
-                reference_frame=reference_frame,
-                timestamps=np.linspace(0, 10, num=100),
-                confidence=np.random.rand(100),
-                confidence_definition=confidence_definition,
-            )
-            pose_estimation_series_list.append(pose_estimation_series)
-
-        camera = nwbfile.create_device(
+        _ = nwbfile.create_device(
             name=f"camera {i}",
             description=f"Camera used to record video {i}",
             manufacturer="No specified manufacturer",
         )
-        try:
-            dimensions = np.array([[video.backend.shape[1], video.backend.shape[2]]])
-        except AttributeError:
-            dimensions = np.array([[400, 400]])
-
-        pose_estimation = PoseEstimation(
-            name="pose_estimation",
-            pose_estimation_series=pose_estimation_series_list,
-            description="Estimated positions of the nodes in the video",
-            original_videos=[video.filename for video in labels.videos],
-            labeled_videos=[video.filename for video in labels.videos],
-            dimensions=dimensions,
-            devices=[camera],
-            scorer="No specified scorer",
-            source_software="SLEAP",
-            source_software_version=sleap_version,
-            skeleton=skeletons_list[0],
-        )
-        nwb_processing_module.add(pose_estimation)
-
     return nwbfile
 
 
@@ -767,6 +720,7 @@ def append_nwb(
             )
         else:
             nwb_file = append_nwb_data(labels, nwb_file, pose_estimation_metadata)
+
         io.write(nwb_file)