diff --git a/bark/generation.py b/bark/generation.py
index f1c32f5..0c0e8da 100644
--- a/bark/generation.py
+++ b/bark/generation.py
@@ -184,10 +184,10 @@ def _load_model(ckpt_path, device, model_type="text"):
         os.path.exists(ckpt_path) and
         _md5(ckpt_path) != REMOTE_MODEL_PATHS[model_type]["checksum"]
     ):
-        print(f"found outdated {model_type} model, removing...")
+        logger.warning(f"found outdated {model_type} model, removing...")
         os.remove(ckpt_path)
     if not os.path.exists(ckpt_path):
-        print(f"{model_type} model not found, downloading...")
+        logger.info(f"{model_type} model not found, downloading...")
         _download(REMOTE_MODEL_PATHS[model_type]["path"], ckpt_path)
     checkpoint = torch.load(ckpt_path, map_location=device)
     # this is a hack
@@ -215,7 +215,7 @@ def _load_model(ckpt_path, device, model_type="text"):
     model.load_state_dict(state_dict, strict=False)
     n_params = model.get_num_params()
     val_loss = checkpoint["best_val_loss"].item()
-    print(f"model loaded: {round(n_params/1e6,1)}M params, {round(val_loss,3)} loss")
+    logger.info(f"model loaded: {round(n_params/1e6,1)}M params, {round(val_loss,3)} loss")
     model.eval()
     model.to(device)
     del checkpoint, state_dict
@@ -346,7 +346,7 @@ def generate_text_semantic(
     device = "cuda" if use_gpu and torch.cuda.device_count() > 0 else "cpu"
     if len(encoded_text) > 256:
         p = round((len(encoded_text) - 256) / len(encoded_text) * 100, 1)
-        print(f"warning, text too long, lopping of last {p}%")
+        logger.warning(f"warning, text too long, lopping of last {p}%")
         encoded_text = encoded_text[:256]
     encoded_text = np.pad(
         encoded_text,