diff --git a/pgx/bridge_bidding.py b/pgx/bridge_bidding.py
index c4c622799..c9639671b 100644
--- a/pgx/bridge_bidding.py
+++ b/pgx/bridge_bidding.py
@@ -37,22 +37,21 @@
 REDOUBLE_ACTION_NUM = 2
 BID_OFFSET_NUM = 3
 
-DDS_RESULTS_TRAIN_URL = "https://drive.google.com/uc?id=1qINu6uIVLJj95oEK3QodsI3aqvOpEozp"
-DDS_RESULTS_TEST_URL = "https://drive.google.com/uc?id=1fNPdJTPw03QrxyOgo-7PvVi5kRI_IZST"
+DDS_RESULTS_TRAIN_SMALL_URL = "https://huggingface.co/datasets/sotetsuk/dds_dataset/resolve/main/dds_results_2.5M.npy"
+DDS_RESULTS_TRAIN_LARGE_URL = "https://huggingface.co/datasets/sotetsuk/dds_dataset/resolve/main/dds_results_10M.npy"
+DDS_RESULTS_TEST_URL = "https://huggingface.co/datasets/sotetsuk/dds_dataset/resolve/main/dds_results_500K.npy"
 
 
 def download_dds_results(download_dir="dds_results"):
     """Download and split the results into 100K chunks."""
-    os.makedirs(download_dir, exist_ok=True)
-    train_fname = os.path.join(download_dir, "dds_results_2.5M.npy")
-    if not os.path.exists(train_fname):
-        _download(DDS_RESULTS_TRAIN_URL, train_fname)
-        with open(train_fname, "rb") as f:
+
+    def split_data(data, prefix, base_i=0):
+        with open(data, "rb") as f:
             keys, values = jnp.load(f)
             n = 100_000
             m = keys.shape[0] // n
             for i in range(m):
-                fname = os.path.join(download_dir, f"train_{i:03d}.npy")
+                fname = os.path.join(download_dir, f"{prefix}_{base_i + i:03d}.npy")
                 with open(fname, "wb") as f:
                     print(
                         f"saving {fname} ... [{i * n}, {(i + 1) * n})",
@@ -66,27 +65,22 @@ def download_dds_results(download_dir="dds_results"):
                         ),
                     )
 
+    os.makedirs(download_dir, exist_ok=True)
+
+    train_small_fname = os.path.join(download_dir, "dds_results_2.5M.npy")
+    if not os.path.exists(train_small_fname):
+        _download(DDS_RESULTS_TRAIN_SMALL_URL, train_small_fname)
+    split_data(train_small_fname, "train")
+
+    train_large_fname = os.path.join(download_dir, "dds_results_10M.npy")
+    if not os.path.exists(train_large_fname):
+        _download(DDS_RESULTS_TRAIN_LARGE_URL, train_large_fname)
+    split_data(train_large_fname, "train", base_i=25)
+
     test_fname = os.path.join(download_dir, "dds_results_500K.npy")
     if not os.path.exists(test_fname):
         _download(DDS_RESULTS_TEST_URL, test_fname)
-        with open(test_fname, "rb") as f:
-            keys, values = jnp.load(f)
-            n = 100_000
-            m = keys.shape[0] // n
-            for i in range(m):
-                fname = os.path.join(download_dir, f"test_{i:03d}.npy")
-                with open(fname, "wb") as f:
-                    print(
-                        f"saving {fname} ... [{i * n}, {(i + 1) * n})",
-                        file=sys.stderr,
-                    )
-                    jnp.save(
-                        f,
-                        (
-                            keys[i * n : (i + 1) * n],
-                            values[i * n : (i + 1) * n],
-                        ),
-                    )
+    split_data(test_fname, "test")
 
 
 @dataclass