@@ -1167,7 +1167,7 @@ def compute_text_embeddings(prompt):
         if args.resume_from_checkpoint != "latest":
             path = os.path.basename(args.resume_from_checkpoint)
         else:
-            # Get the mos recent checkpoint
+            # Get the most recent checkpoint
             dirs = os.listdir(args.output_dir)
             dirs = [d for d in dirs if d.startswith("checkpoint")]
             dirs = sorted(dirs, key=lambda x: int(x.split("-")[1]))
@@ -1364,7 +1364,7 @@ def compute_text_embeddings(prompt):
             if global_step >= args.max_train_steps:
                 break
 
-    # Create the pipeline using using the trained modules and save it.
+    # Create the pipeline using the trained modules and save it.
     accelerator.wait_for_everyone()
     if accelerator.is_main_process:
         pipeline_args = {}