diff --git a/misc/GREW/README.md b/misc/GREW/README.md
index e314e5a..985781f 100644
--- a/misc/GREW/README.md
+++ b/misc/GREW/README.md
@@ -70,9 +70,9 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node
 
 ## Get the submission file
 ```shell
-CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 lib/main.py --cfgs ./misc/HID/baseline_hid.yaml --phase test
+CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 lib/main.py --cfgs ./config/baseline_GREW.yaml --phase test
 ```
 The result will be generated in your working directory, you must rename and compress it as the requirements before submitting.
 
 ## Evaluation locally
-While the original grew treat both seq_01 and seq_02 as gallery, but there is no ground truth for probe. Therefore, it is nessesary to upload the submission file on grew competitation. We seperate test set to: seq_01 as gallery, seq_02 as probe. Then you can modify `eval_func` in the `./config/baseline_GREW.yaml` to `identification_real_scene`, you can obtain result localy like setting of OUMVLP. 
\ No newline at end of file
+While the original grew treat both seq_01 and seq_02 as gallery, but there is no ground truth for probe. Therefore, it is nessesary to upload the submission file on grew competitation. We seperate test set to: seq_01 as gallery, seq_02 as probe. Then you can modify `eval_func` in the `./config/baseline_GREW.yaml` to `identification_real_scene`, you can obtain result localy like setting of OUMVLP.