diff --git a/.idea/workspace.xml b/.idea/workspace.xml
new file mode 100644
index 0000000..353b0fc
--- /dev/null
+++ b/.idea/workspace.xml
@@ -0,0 +1,70 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="AutoImportSettings">
+    <option name="autoReloadType" value="SELECTIVE" />
+  </component>
+  <component name="ChangeListManager">
+    <list default="true" id="079f724a-dabb-42e0-84ee-a850f914d5ae" name="Changes" comment="">
+      <change beforePath="$PROJECT_DIR$/space-1/README.md" beforeDir="false" afterPath="$PROJECT_DIR$/space-1/README.md" afterDir="false" />
+      <change beforePath="$PROJECT_DIR$/space-2/README.md" beforeDir="false" afterPath="$PROJECT_DIR$/space-2/README.md" afterDir="false" />
+    </list>
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="Git.Settings">
+    <option name="RECENT_GIT_ROOT_PATH" value="$PROJECT_DIR$" />
+  </component>
+  <component name="MarkdownSettingsMigration">
+    <option name="stateVersion" value="1" />
+  </component>
+  <component name="ProjectId" id="2Mb9j54td8k53KgHRf98pcsfkaC" />
+  <component name="ProjectViewState">
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
+  <component name="PropertiesComponent">
+    <property name="RunOnceActivity.OpenProjectViewOnStart" value="true" />
+    <property name="RunOnceActivity.ShowReadmeOnStart" value="true" />
+    <property name="WebServerToolWindowFactoryState" value="true" />
+    <property name="last_opened_file_path" value="$PROJECT_DIR$/space-2" />
+    <property name="node.js.detected.package.eslint" value="true" />
+    <property name="node.js.detected.package.tslint" value="true" />
+    <property name="node.js.selected.package.eslint" value="(autodetect)" />
+    <property name="node.js.selected.package.tslint" value="(autodetect)" />
+  </component>
+  <component name="RecentsManager">
+    <key name="CopyFile.RECENT_KEYS">
+      <recent name="$PROJECT_DIR$/space-2" />
+    </key>
+  </component>
+  <component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
+  <component name="TaskManager">
+    <task active="true" id="Default" summary="Default task">
+      <changelist id="079f724a-dabb-42e0-84ee-a850f914d5ae" name="Changes" comment="" />
+      <created>1678025547077</created>
+      <option name="number" value="Default" />
+      <option name="presentableId" value="Default" />
+      <updated>1678025547077</updated>
+      <workItem from="1678025548212" duration="147000" />
+      <workItem from="1678025785276" duration="1409000" />
+      <workItem from="1678296002630" duration="833000" />
+    </task>
+    <servers />
+  </component>
+  <component name="TypeScriptGeneratedFilesManager">
+    <option name="version" value="3" />
+  </component>
+  <component name="Vcs.Log.Tabs.Properties">
+    <option name="TAB_STATES">
+      <map>
+        <entry key="MAIN">
+          <value>
+            <State />
+          </value>
+        </entry>
+      </map>
+    </option>
+  </component>
+</project>
\ No newline at end of file
diff --git a/space-1/README.md b/space-1/README.md
index a734388..abc715c 100644
--- a/space-1/README.md
+++ b/space-1/README.md
@@ -57,11 +57,11 @@ The downloaded zip file `data.zip` contains pre-training corpora and four TOD be
 
 ## Pre-training
 ### Pre-training Corpora
-- [UniDA](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE1.0/Pre-training%20Data.zip): a new labeled dialog dataset consisting of 975,780 utterances, which are annotated with 20 frequently-used DAs, according to our proposed comprehensive unified DA taxonomy for task-oriented dialog.
-- [UnDial](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE1.0/Pre-training%20Data.zip): a large-scale unlabeled dialog dataset consisting of 35M utterances with careful processing, ranging from online forum chatting logs to customer service conversations.
+- [UniDA](https://drive.google.com/file/d/146ZPNI_FDKNX0xd_iErmD8etA5yj5mox/view?usp=share_link): a new labeled dialog dataset consisting of 975,780 utterances, which are annotated with 20 frequently-used DAs, according to our proposed comprehensive unified DA taxonomy for task-oriented dialog.
+- [UnDial](https://drive.google.com/file/d/1-1CEyd1gPJL8r9Na6aD9Wq0mHg-fAaI8/view?usp=share_link): a large-scale unlabeled dialog dataset consisting of 35M utterances with careful processing, ranging from online forum chatting logs to customer service conversations.
 
 ### Pre-trained Checkpoint
-- [SPACE1.0](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE1.0/model.zip): an uncased model with DA classification head (12-layers, 768-hidden, 12-heads, 109M parameters)
+- [SPACE1.0](https://drive.google.com/file/d/18NPZQ6SH9Q0nFZenf_hNyuJTyT9IFAjL/view?usp=share_link): an uncased model with DA classification head (12-layers, 768-hidden, 12-heads, 109M parameters)
 
 You need to unzip the downloaded model file `model.zip`, then put the unzipped directory `model` into the project directory `SPACE1.0` for the further fine-tuning.
 
@@ -84,7 +84,7 @@ sh scripts/pre_train/train_multi.sh
 
 ## Fine-tuning
 ### Fine-tuned Checkpoints
-Download checkpoints from this [link](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE1.0/outputs.zip). 
+Download checkpoints from this [link](https://drive.google.com/file/d/1JerSwvLzes6b-igQ7lPCTIrh6IvrTMK6/view?usp=share_link). 
 
 The downloaded zip file `outputs.zip` contains our best fine-tuned checkpoints on different datasets: 
 - the **7-th** epoch on MultiWOZ2.0 (**60** training epochs in total)
diff --git a/space-2/README.md b/space-2/README.md
index c7979ae..3b4a713 100644
--- a/space-2/README.md
+++ b/space-2/README.md
@@ -49,11 +49,11 @@ SAVE_ROOT=<YOUR_SAVE_PATH>/${PROJECT_NAME}  # root path of model's output
 ```
 
 ### Data Preparation
-Download data-split1 from this [link](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/data.zip). 
+Download data-split1 from this [link](https://drive.google.com/file/d/1ocwnuOLxB3VzngeWZsm59IRrhEv22Scx/view?usp=share_link). 
 
 The downloaded zip file `data.zip` contains pre-training corpora (including BANKING77, CLINC150 and HWU64) and three extra task-oriented (TOD) benchmark datasets: REST8K, DSTC8 and TOP, which have already been processed. You need to put the unzipped directory `data` into the project directory `SPACE2.0` for the subsequent training.
 
-Download data-split2 from this [link](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/trippy/data.zip).
+Download data-split2 from this [link](https://drive.google.com/file/d/1BZvlARzxXobjpQQRWvkF3jwnLN9-9c-n/view?usp=share_link).
 
 The downloaded zip file `data.zip` contains one TOD benchmark dataset: MultiWOZ2.1, which have already been processed. You need to put the unzipped directory `data` into the directory `SPACE2.0/trippy` for the subsequent training.
 
@@ -77,12 +77,12 @@ SPACE2.0/
 
 ## Pre-training
 ### Pre-training Corpora
-- [AnPreDial](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/AnPreDial.zip): a new labeled dialog dataset annotated with semantic trees, which contains 32 existing labeled TOD datasets with 3
+- [AnPreDial](https://drive.google.com/file/d/1ocwnuOLxB3VzngeWZsm59IRrhEv22Scx/view?usp=share_link): a new labeled dialog dataset annotated with semantic trees, which contains 32 existing labeled TOD datasets with 3
 million turns, ranging from single-turn QA to multi-turn dialogs.
-- [UnPreDial](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/UnPreDial.zip): a large-scale unlabeled dialog dataset consisting of 19M utterances with careful processing from 21 online dialog corpora, ranging from online forums to conversational machine reading comprehension.
+- [UnPreDial](https://drive.google.com/file/d/1ocwnuOLxB3VzngeWZsm59IRrhEv22Scx/view?usp=share_link): a large-scale unlabeled dialog dataset consisting of 19M utterances with careful processing from 21 online dialog corpora, ranging from online forums to conversational machine reading comprehension.
 
 ### Pre-trained Checkpoint
-- [SPACE2.0](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/model.zip): an uncased model (12-layers, 768-hidden, 12-heads, 110M parameters)
+- [SPACE2.0](https://drive.google.com/file/d/1QOhrd_kB8VXevEAo1Gohr58LxMI4OjYo/view?usp=share_link): an uncased model (12-layers, 768-hidden, 12-heads, 110M parameters)
 
 You need to unzip the downloaded model file `model.zip`, then put the unzipped directory `model` into the project directory `SPACE2.0` for the further fine-tuning.
 
@@ -100,7 +100,7 @@ sh scripts/pre_train/train.sh
 
 ## Fine-tuning
 ### Fine-tuned Checkpoints
-Download checkpoints-split1 from this [link](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/outputs.zip). 
+Download checkpoints-split1 from this [link](https://drive.google.com/file/d/10QEEMNsjO5rH0ZRsJBj9zkDc5ozxc3Ch/view?usp=share_link). 
 
 The downloaded zip file `outputs.zip` contains our best fine-tuned checkpoints on the following six datasets: 
 - BANKING77, CLINC150, HWU64 (**Intent Prediction**)
@@ -109,7 +109,7 @@ The downloaded zip file `outputs.zip` contains our best fine-tuned checkpoints o
 
 If you want to reproduce our reported results, you should put the unzipped directory `outputs` into the directory `${SAVE_ROOT}` (set in scripts). 
 
-Download checkpoints-split2 from this [link](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/trippy/outputs.zip). 
+Download checkpoints-split2 from this [link](https://drive.google.com/file/d/1G7K6AIBcRTC3CgMtSZdJ_TM6rFeXGe96/view?usp=share_link). 
 
 The downloaded zip file `outputs.zip` contains our best fine-tuned checkpoints on one dataset: 
 - MultiWOZ2.1 (**Dialog State Tracking**)
@@ -159,7 +159,7 @@ sh scripts/multiwoz21/train.sh
 
 > **NOTE**: You can skip Step 1 if you directly download the output model of Step 1. 
 > For DST task, you should convert model parameters into Hugging Face format.
-> So you can download the model file from this [link](http://datarepo0.oss-cn-hangzhou-zmf.aliyuncs.com/Alibaba/SPACE2/trippy/model.zip) directly.
+> So you can download the model file from this [link](https://drive.google.com/file/d/1xzKhKBg0hJPAq1NebluLIwfVxnfN1-1R/view?usp=share_link) directly.
 > Then you need to unzip the downloaded model file `model.zip`, and put the unzipped directory `model` into the directory `SPACE2.0/trippy` for the further fine-tuning.
 
 ### Inference