diff --git a/llms/mlx_lm/utils.py b/llms/mlx_lm/utils.py
index 8893b570..d4afd428 100644
--- a/llms/mlx_lm/utils.py
+++ b/llms/mlx_lm/utils.py
@@ -61,8 +61,8 @@ def wired_limit(model: nn.Module, streams: Optional[List[mx.Stream]] = None):
         model_mb = model_bytes // 2**20
         max_rec_mb = max_rec_size // 2**20
         print(
-            "[WARNING] Generating with a model that requires {model_mb} MB "
-            "which is close to the maximum recommended size of {max_rec_mb} "
+            f"[WARNING] Generating with a model that requires {model_mb} MB "
+            f"which is close to the maximum recommended size of {max_rec_mb} "
             "MB. This can be slow. See the documentation for possible work-arounds: "
             "https://github.com/ml-explore/mlx-examples/tree/main/llms#large-models"
         )
diff --git a/stable_diffusion/image2image.py b/stable_diffusion/image2image.py
index e470aa81..4444c488 100644
--- a/stable_diffusion/image2image.py
+++ b/stable_diffusion/image2image.py
@@ -30,6 +30,7 @@ if __name__ == "__main__":
     parser.add_argument("--preload-models", action="store_true")
     parser.add_argument("--output", default="out.png")
     parser.add_argument("--verbose", "-v", action="store_true")
+    parser.add_argument("--seed", type=int)
     args = parser.parse_args()
 
     # Load the models
@@ -94,6 +95,7 @@ if __name__ == "__main__":
         cfg_weight=args.cfg,
         num_steps=args.steps,
         negative_text=args.negative_prompt,
+        seed=args.seed,
     )
     for x_t in tqdm(latents, total=int(args.steps * args.strength)):
         mx.eval(x_t)