diff --git a/.circleci/config.yml b/.circleci/config.yml
index 917c5f0ab..577315f08 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -334,7 +334,7 @@ jobs:
             coverage run flood_forecast/trainer.py -p tests/dsanet.json
             echo -e 'running trainer_decoder_test \n'
             coverage run flood_forecast/trainer.py -p tests/decoder_test.json
-            echo -e 'running trainer_full_transformer_test \n'
+            echo -e 'running trainer_full_transformer_test'
             coverage run flood_forecast/trainer.py -p  tests/full_transformer.json
         
       - store_test_results:
diff --git a/flood_forecast/transformer_xl/cross_former.py b/flood_forecast/transformer_xl/cross_former.py
index cba0e7552..50c082b20 100644
--- a/flood_forecast/transformer_xl/cross_former.py
+++ b/flood_forecast/transformer_xl/cross_former.py
@@ -19,6 +19,7 @@ def __init__(
         e_layers=3,
         dropout=0.0,
         baseline=False,
+        n_targs=None,
         device=torch.device("cuda:0"),
     ):
         """Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting.
@@ -57,6 +58,7 @@ def __init__(
         self.out_len = forecast_length
         self.seg_len = seg_len
         self.merge_win = win_size
+        self.n_targs = n_time_series if n_targs is None else n_targs
 
         self.baseline = baseline
 
@@ -126,7 +128,9 @@ def forward(self, x_seq: torch.Tensor):
         )
         predict_y = self.decoder(dec_in, enc_out)
 
-        return base + predict_y[:, : self.out_len, :]
+        result = base + predict_y[:, : self.out_len, :]
+        res = result[:, :, :self.n_targs]
+        return res
 
 
 class SegMerging(nn.Module):