Refactor: Inferring number of dimensions

main.py

@@ -58,13 +58,14 @@ if not exists('images.fbin'):
         image_embedding = model.encode_image(image_data).detach().numpy()
         vectors.append(image_embedding)
 
-    image_mat = np.concatenate(vectors)
+    image_mat = np.vstack(vectors)
     save_matrix(image_mat, 'images.fbin')
 
 if not exists('images.usearch'):
-    index = Index(ndim=256, metric=MetricKind.Cos)
     image_mat = load_matrix('images.fbin')
     count = image_mat.shape[0]
+    ndim = image_mat.shape[1]
+    index = Index(ndim=ndim, metric=MetricKind.Cos)
 
     for idx in tqdm(range(count), desc='Indexing vectors'):
         index.add(idx, image_mat[idx, :].flatten())