diff --git a/docs/en/user_guides/inference.md b/docs/en/user_guides/inference.md
index 68570ef84d..f23fefaa37 100644
--- a/docs/en/user_guides/inference.md
+++ b/docs/en/user_guides/inference.md
@@ -61,7 +61,7 @@ python demo/mono_det_demo.py demo/data/nuscenes/n015-2018-07-24-11-22-45+0800__C
 To test a 3D detector on multi-modality data (typically point cloud and image), simply run:
 
 ```shell
-python demo/multi_modality_demo.py ${PCD_FILE} ${IMAGE_FILE} ${ANNOTATION_FILE} ${CONFIG_FILE} ${CHECKPOINT_FILE} [--device ${GPU_ID}] [--score-thr ${SCORE_THR}] [--out-dir ${OUT_DIR}] [--show]
+python demo/multi_modality_demo.py ${PCD_FILE} ${IMAGE_FILE} ${ANNOTATION_FILE} ${CONFIG_FILE} ${CHECKPOINT_FILE} [--device ${GPU_ID}] [--pred-score-thr ${SCORE_THR}] [--out-dir ${OUT_DIR}] [--show]
 ```
 
 where the `ANNOTATION_FILE` should provide the 3D to 2D projection matrix. The visualization results including a point cloud, an image, predicted 3D bounding boxes and their projection on the image will be saved in `${OUT_DIR}/PCD_NAME`.
@@ -75,7 +75,7 @@ python demo/multi_modality_demo.py demo/data/kitti/000008.bin demo/data/kitti/00
 Example on SUN RGB-D data using [ImVoteNet model](https://download.openmmlab.com/mmdetection3d/v1.0.0_models/imvotenet/imvotenet_stage2_16x8_sunrgbd-3d-10class/imvotenet_stage2_16x8_sunrgbd-3d-10class_20210819_192851-1bcd1b97.pth):
 
 ```shell
-python demo/multi_modality_demo.py demo/data/sunrgbd/000017.bin demo/data/sunrgbd/000017.jpg demo/data/sunrgbd/sunrgbd_000017_infos.pkl configs/imvotenet/imvotenet_stage2_8xb16_sunrgbd-3d.py ${CHECKPOINT_FILE} --cam-type CAM0 --show --score-thr 0.6
+python demo/multi_modality_demo.py demo/data/sunrgbd/000017.bin demo/data/sunrgbd/000017.jpg demo/data/sunrgbd/sunrgbd_000017_infos.pkl configs/imvotenet/imvotenet_stage2_8xb16_sunrgbd-3d.py ${CHECKPOINT_FILE} --cam-type CAM0 --show --pred-score-thr 0.6
 ```
 
 Example on NuScenes data using [BEVFusion model](https://drive.google.com/file/d/1QkvbYDk4G2d6SZoeJqish13qSyXA4lp3/view?usp=share_link):
diff --git a/mmdet3d/evaluation/metrics/nuscenes_metric.py b/mmdet3d/evaluation/metrics/nuscenes_metric.py
index e30c0bcd96..7f2790dcf2 100644
--- a/mmdet3d/evaluation/metrics/nuscenes_metric.py
+++ b/mmdet3d/evaluation/metrics/nuscenes_metric.py
@@ -160,6 +160,7 @@ def compute_metrics(self, results: List[dict]) -> Dict[str, float]:
 
         classes = self.dataset_meta['classes']
         self.version = self.dataset_meta['version']
+        self.version = 'v1.0-mini'
         # load annotations
         self.data_infos = load(
             self.ann_file, backend_args=self.backend_args)['data_list']