diff --git a/paddleocr.py b/paddleocr.py
index 8e34c4fbc331f798618fc5f33bc00963a577e25a..f6318ad20fb68c5f22bc9d8cfe8ff77fd67cd696 100644
--- a/paddleocr.py
+++ b/paddleocr.py
@@ -289,7 +289,8 @@ MODEL_URLS = {
                 'ch': {
                     'url':
                     'https://paddleocr.bj.bcebos.com/ppstructure/models/layout/picodet_lcnet_x1_0_layout_infer.tar',
-                    'dict_path': 'ppocr/utils/dict/layout_publaynet_dict.txt'
+                    'dict_path':
+                    'ppocr/utils/dict/layout_dict/layout_publaynet_dict.txt'
                 }
             }
         }
diff --git a/ppstructure/docs/models_list.md b/ppstructure/docs/models_list.md
index ef2994cabea38709464780d25b5f32c3b9801b4c..0b2f41deb5588c82238e93d835dc8c606e4fde2e 100644
--- a/ppstructure/docs/models_list.md
+++ b/ppstructure/docs/models_list.md
@@ -34,8 +34,8 @@
 
 |模型名称|模型简介|推理模型大小|下载地址|
 | --- | --- | --- | --- |
-|en_ppocr_mobile_v2.0_table_structure|基于TableRec-RARE在PubTabNet数据集上训练的英文表格识别模型|18.6M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar) |
-|en_ppstructure_mobile_v2.0_SLANet|基于SLANet在PubTabNet数据集上训练的英文表格识别模型|9M|[推理模型](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_train.tar) |
+|en_ppocr_mobile_v2.0_table_structure|基于TableRec-RARE在PubTabNet数据集上训练的英文表格识别模型|6.8M|[推理模型](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar) |
+|en_ppstructure_mobile_v2.0_SLANet|基于SLANet在PubTabNet数据集上训练的英文表格识别模型|9.2M|[推理模型](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_train.tar) |
 |ch_ppstructure_mobile_v2.0_SLANet|基于SLANet在PubTabNet数据集上训练的中文表格识别模型|9.3M|[推理模型](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar) / [训练模型](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_train.tar) |
 
 <a name="3"></a>
diff --git a/ppstructure/docs/models_list_en.md b/ppstructure/docs/models_list_en.md
index 64a7cdebc3e3c7ac18ae2f61013aa4e8a7c3ead8..91f3286bf1d260e7a582be62e637293937a534cc 100644
--- a/ppstructure/docs/models_list_en.md
+++ b/ppstructure/docs/models_list_en.md
@@ -35,8 +35,8 @@ If you need to use other OCR models, you can download the model in [PP-OCR model
 
 |model| description                                                                 |inference model size|download|
 | --- |-----------------------------------------------------------------------------| --- | --- |
-|en_ppocr_mobile_v2.0_table_structure| English table recognition model trained on PubTabNet dataset based on TableRec-RARE |18.6M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar) |
-|en_ppstructure_mobile_v2.0_SLANet|English table recognition model trained on PubTabNet dataset based on SLANet|9M|[inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_train.tar) |
+|en_ppocr_mobile_v2.0_table_structure| English table recognition model trained on PubTabNet dataset based on TableRec-RARE |6.8M|[inference model](https://paddleocr.bj.bcebos.com/dygraph_v2.0/table/en_ppocr_mobile_v2.0_table_structure_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/dygraph_v2.1/table/en_ppocr_mobile_v2.0_table_structure_train.tar) |
+|en_ppstructure_mobile_v2.0_SLANet|English table recognition model trained on PubTabNet dataset based on SLANet|9.2M|[inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/en_ppstructure_mobile_v2.0_SLANet_train.tar) |
 |ch_ppstructure_mobile_v2.0_SLANet|Chinese table recognition model trained on PubTabNet dataset based on SLANet|9.3M|[inference model](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_infer.tar) / [trained model](https://paddleocr.bj.bcebos.com/ppstructure/models/slanet/ch_ppstructure_mobile_v2.0_SLANet_train.tar) |
 
 <a name="3"></a>
diff --git a/tools/infer/utility.py b/tools/infer/utility.py
index 1eebc73f31e6b48a473c20d907ca401ad919fe0b..1355ca62e5c6b50177d1c7c2f6d7a016e168f545 100644
--- a/tools/infer/utility.py
+++ b/tools/infer/utility.py
@@ -181,14 +181,21 @@ def create_predictor(args, mode, logger):
         return sess, sess.get_inputs()[0], None, None
 
     else:
-        model_file_path = model_dir + "/inference.pdmodel"
-        params_file_path = model_dir + "/inference.pdiparams"
+        file_names = ['model', 'inference']
+        for file_name in file_names:
+            model_file_path = '{}/{}.pdmodel'.format(model_dir, file_name)
+            params_file_path = '{}/{}.pdiparams'.format(model_dir, file_name)
+            if os.path.exists(model_file_path) and os.path.exists(
+                    params_file_path):
+                break
         if not os.path.exists(model_file_path):
-            raise ValueError("not find model file path {}".format(
-                model_file_path))
+            raise ValueError(
+                "not find model.pdmodel or inference.pdmodel in {}".format(
+                    model_dir))
         if not os.path.exists(params_file_path):
-            raise ValueError("not find params file path {}".format(
-                params_file_path))
+            raise ValueError(
+                "not find model.pdiparams or inference.pdiparams in {}".format(
+                    model_dir))
 
         config = inference.Config(model_file_path, params_file_path)