diff --git a/examples/finetune/finetune.cpp b/examples/finetune/finetune.cpp
index 17b89a2f8..d0fc48f23 100644
--- a/examples/finetune/finetune.cpp
+++ b/examples/finetune/finetune.cpp
@@ -250,8 +250,11 @@ static void init_model(struct llama_model * input, struct my_llama_model * model
     model->norm           = llama_get_model_tensor(input, tn(LLM_TENSOR_OUTPUT_NORM));
     model->output         = llama_get_model_tensor(input, tn(LLM_TENSOR_OUTPUT));
 
-    model->layers.resize(hparams.n_layer);
+    assert_shape_2d(model->tok_embeddings, hparams.n_embd, hparams.n_vocab);
+    assert_shape_1d(model->norm,           hparams.n_embd);
+    assert_shape_2d(model->output,         hparams.n_embd, hparams.n_vocab);
 
+    model->layers.resize(hparams.n_layer);
     for (uint32_t i = 0; i < hparams.n_layer; ++i) {
         auto & layer = model->layers[i];
 
@@ -264,6 +267,16 @@ static void init_model(struct llama_model * input, struct my_llama_model * model
         layer.w1             = llama_get_model_tensor(input, tni(LLM_TENSOR_FFN_GATE, i));
         layer.w2             = llama_get_model_tensor(input, tni(LLM_TENSOR_FFN_DOWN, i));
         layer.w3             = llama_get_model_tensor(input, tni(LLM_TENSOR_FFN_UP, i));
+
+        assert_shape_1d(layer.attention_norm, hparams.n_embd);
+        assert_shape_2d(layer.wq,             hparams.n_embd, hparams.n_embd);
+        assert_shape_2d(layer.wk,             hparams.n_embd, hparams.n_embd);
+        assert_shape_2d(layer.wv,             hparams.n_embd, hparams.n_embd);
+        assert_shape_2d(layer.wo,             hparams.n_embd, hparams.n_embd);
+        assert_shape_1d(layer.ffn_norm,       hparams.n_embd);
+        assert_shape_2d(layer.w1,             hparams.n_embd, hparams.n_ff);
+        assert_shape_2d(layer.w2,             hparams.n_ff,   hparams.n_embd);
+        assert_shape_2d(layer.w3,             hparams.n_embd, hparams.n_ff);
     }
 }