From b53779df761686fd51c812cab01e9b56f77e13b9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E9=AA=91=E9=A9=AC=E5=B0=8F=E7=8C=AB?= <1435130236@qq.com>
Date: Mon, 28 Nov 2022 13:33:11 +0800
Subject: [PATCH] community models: fix testing bug (#5678)

* update project

* update icon and keyword

* fix running bug

* fix conflict
---
 .../allenai/macaw-large/introduction_cn.ipynb          |  3 ++-
 .../allenai/macaw-large/introduction_en.ipynb          |  3 ++-
 .../community/allenai/specter/introduction_cn.ipynb    |  4 ++--
 .../community/allenai/specter/introduction_en.ipynb    |  4 ++--
 .../ms-marco-MiniLM-L-12-v2/introduction_cn.ipynb      |  4 ++--
 .../ms-marco-MiniLM-L-12-v2/introduction_en.ipynb      |  4 ++--
 .../ms-marco-TinyBERT-L-2/introduction_cn.ipynb        | 10 +++++++---
 .../ms-marco-TinyBERT-L-2/introduction_en.ipynb        | 10 +++++++---
 .../nli-MiniLM2-L6-H768/introduction_cn.ipynb          |  4 ++--
 .../nli-MiniLM2-L6-H768/introduction_en.ipynb          |  4 ++--
 .../stsb-TinyBERT-L-4/introduction_cn.ipynb            |  4 ++--
 .../stsb-TinyBERT-L-4/introduction_en.ipynb            |  4 ++--
 .../Bio_ClinicalBERT/introduction_cn.ipynb             |  4 ++--
 .../Bio_ClinicalBERT/introduction_en.ipynb             |  4 ++--
 .../google/t5-base-lm-adapt/introduction_cn.ipynb      |  3 ++-
 .../google/t5-base-lm-adapt/introduction_en.ipynb      |  3 ++-
 .../google/t5-large-lm-adapt/introduction_cn.ipynb     |  3 ++-
 .../google/t5-large-lm-adapt/introduction_en.ipynb     |  3 ++-
 .../google/t5-small-lm-adapt/introduction_cn.ipynb     |  3 ++-
 .../google/t5-small-lm-adapt/introduction_en.ipynb     |  3 ++-
 .../google/t5-v1_1-base/introduction_cn.ipynb          |  3 ++-
 .../google/t5-v1_1-base/introduction_en.ipynb          |  3 ++-
 .../google/t5-v1_1-large/introduction_cn.ipynb         |  3 ++-
 .../google/t5-v1_1-large/introduction_en.ipynb         |  3 ++-
 .../google/t5-v1_1-small/introduction_cn.ipynb         |  3 ++-
 .../google/t5-v1_1-small/introduction_en.ipynb         |  3 ++-
 26 files changed, 62 insertions(+), 40 deletions(-)

diff --git a/modelcenter/community/allenai/macaw-large/introduction_cn.ipynb b/modelcenter/community/allenai/macaw-large/introduction_cn.ipynb
index 905d2152..0a947b84 100644
--- a/modelcenter/community/allenai/macaw-large/introduction_cn.ipynb
+++ b/modelcenter/community/allenai/macaw-large/introduction_cn.ipynb
@@ -53,7 +53,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"allenai/macaw-large\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/allenai/macaw-large/introduction_en.ipynb b/modelcenter/community/allenai/macaw-large/introduction_en.ipynb
index 440ebda1..3cf34027 100644
--- a/modelcenter/community/allenai/macaw-large/introduction_en.ipynb
+++ b/modelcenter/community/allenai/macaw-large/introduction_en.ipynb
@@ -53,7 +53,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"allenai/macaw-large\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/allenai/specter/introduction_cn.ipynb b/modelcenter/community/allenai/specter/introduction_cn.ipynb
index 32ced08c..53c1a209 100644
--- a/modelcenter/community/allenai/specter/introduction_cn.ipynb
+++ b/modelcenter/community/allenai/specter/introduction_cn.ipynb
@@ -44,9 +44,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertModel\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"allenai/specter\")\n",
+    "model = BertModel.from_pretrained(\"allenai/specter\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/allenai/specter/introduction_en.ipynb b/modelcenter/community/allenai/specter/introduction_en.ipynb
index a77c6968..c210f335 100644
--- a/modelcenter/community/allenai/specter/introduction_en.ipynb
+++ b/modelcenter/community/allenai/specter/introduction_en.ipynb
@@ -44,9 +44,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertModel\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"allenai/specter\")\n",
+    "model = BertModel.from_pretrained(\"allenai/specter\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_cn.ipynb b/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_cn.ipynb
index 1f1adfe0..405f5ab5 100644
--- a/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_cn.ipynb
+++ b/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_cn.ipynb
@@ -50,9 +50,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertForSequenceClassification\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/ms-marco-MiniLM-L-12-v2\")\n",
+    "model = BertForSequenceClassification.from_pretrained(\"cross-encoder/ms-marco-MiniLM-L-12-v2\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_en.ipynb b/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_en.ipynb
index 0389e1e2..6868bfa7 100644
--- a/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_en.ipynb
+++ b/modelcenter/community/cross-encoder/ms-marco-MiniLM-L-12-v2/introduction_en.ipynb
@@ -50,9 +50,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertForSequenceClassification\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/ms-marco-MiniLM-L-12-v2\")\n",
+    "model = BertForSequenceClassification.from_pretrained(\"cross-encoder/ms-marco-MiniLM-L-12-v2\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_cn.ipynb b/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_cn.ipynb
index 84472703..4ced6196 100644
--- a/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_cn.ipynb
+++ b/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_cn.ipynb
@@ -50,9 +50,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertModel\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/ms-marco-TinyBERT-L-2\")\n",
+    "model = BertModel.from_pretrained(\"cross-encoder/ms-marco-TinyBERT-L-2\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
@@ -103,7 +103,11 @@
    ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }
diff --git a/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_en.ipynb b/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_en.ipynb
index b3862b25..99f02830 100644
--- a/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_en.ipynb
+++ b/modelcenter/community/cross-encoder/ms-marco-TinyBERT-L-2/introduction_en.ipynb
@@ -50,9 +50,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertModel\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/ms-marco-TinyBERT-L-2\")\n",
+    "model = BertModel.from_pretrained(\"cross-encoder/ms-marco-TinyBERT-L-2\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
@@ -103,7 +103,11 @@
    ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }
diff --git a/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_cn.ipynb b/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_cn.ipynb
index b7393f4f..8eef3fe3 100644
--- a/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_cn.ipynb
+++ b/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_cn.ipynb
@@ -61,9 +61,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import RobertaForSequenceClassification\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/nli-MiniLM2-L6-H768\")\n",
+    "model = RobertaForSequenceClassification.from_pretrained(\"cross-encoder/nli-MiniLM2-L6-H768\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_en.ipynb b/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_en.ipynb
index c62c2aff..859faaee 100644
--- a/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_en.ipynb
+++ b/modelcenter/community/cross-encoder/nli-MiniLM2-L6-H768/introduction_en.ipynb
@@ -61,9 +61,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import RobertaForSequenceClassification\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/nli-MiniLM2-L6-H768\")\n",
+    "model = RobertaForSequenceClassification.from_pretrained(\"cross-encoder/nli-MiniLM2-L6-H768\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_cn.ipynb b/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_cn.ipynb
index 53b39a12..52c0e0e4 100644
--- a/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_cn.ipynb
+++ b/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_cn.ipynb
@@ -156,9 +156,9 @@
    ],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertForSequenceClassification\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/stsb-TinyBERT-L-4\")\n",
+    "model = BertForSequenceClassification.from_pretrained(\"cross-encoder/stsb-TinyBERT-L-4\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_en.ipynb b/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_en.ipynb
index 0183f00b..4a4c4259 100644
--- a/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_en.ipynb
+++ b/modelcenter/community/cross-encoder/stsb-TinyBERT-L-4/introduction_en.ipynb
@@ -52,9 +52,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertForSequenceClassification\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"cross-encoder/stsb-TinyBERT-L-4\")\n",
+    "model = BertForSequenceClassification.from_pretrained(\"cross-encoder/stsb-TinyBERT-L-4\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_cn.ipynb b/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_cn.ipynb
index 7064ebfb..46d871dd 100644
--- a/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_cn.ipynb
+++ b/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_cn.ipynb
@@ -50,9 +50,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertForMaskedLM\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"emilyalsentzer/Bio_ClinicalBERT\")\n",
+    "model = BertForMaskedLM.from_pretrained(\"emilyalsentzer/Bio_ClinicalBERT\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_en.ipynb b/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_en.ipynb
index fab51acf..faab51f8 100644
--- a/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_en.ipynb
+++ b/modelcenter/community/emilyalsentzer/Bio_ClinicalBERT/introduction_en.ipynb
@@ -50,9 +50,9 @@
    "outputs": [],
    "source": [
     "import paddle\n",
-    "from paddlenlp.transformers import AutoModel\n",
+    "from paddlenlp.transformers import BertForMaskedLM\n",
     "\n",
-    "model = AutoModel.from_pretrained(\"emilyalsentzer/Bio_ClinicalBERT\")\n",
+    "model = BertForMaskedLM.from_pretrained(\"emilyalsentzer/Bio_ClinicalBERT\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
     "print(model(input_ids))"
    ]
diff --git a/modelcenter/community/google/t5-base-lm-adapt/introduction_cn.ipynb b/modelcenter/community/google/t5-base-lm-adapt/introduction_cn.ipynb
index 8e4a107f..8f6246a2 100644
--- a/modelcenter/community/google/t5-base-lm-adapt/introduction_cn.ipynb
+++ b/modelcenter/community/google/t5-base-lm-adapt/introduction_cn.ipynb
@@ -66,7 +66,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-base-lm-adapt\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-base-lm-adapt/introduction_en.ipynb b/modelcenter/community/google/t5-base-lm-adapt/introduction_en.ipynb
index c1a17778..adf7431e 100644
--- a/modelcenter/community/google/t5-base-lm-adapt/introduction_en.ipynb
+++ b/modelcenter/community/google/t5-base-lm-adapt/introduction_en.ipynb
@@ -66,7 +66,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-base-lm-adapt\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-large-lm-adapt/introduction_cn.ipynb b/modelcenter/community/google/t5-large-lm-adapt/introduction_cn.ipynb
index ce6a76d6..b554bc5d 100644
--- a/modelcenter/community/google/t5-large-lm-adapt/introduction_cn.ipynb
+++ b/modelcenter/community/google/t5-large-lm-adapt/introduction_cn.ipynb
@@ -74,7 +74,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-large-lm-adapt\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-large-lm-adapt/introduction_en.ipynb b/modelcenter/community/google/t5-large-lm-adapt/introduction_en.ipynb
index fdc71cd1..ce7308d4 100644
--- a/modelcenter/community/google/t5-large-lm-adapt/introduction_en.ipynb
+++ b/modelcenter/community/google/t5-large-lm-adapt/introduction_en.ipynb
@@ -74,7 +74,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-large-lm-adapt\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-small-lm-adapt/introduction_cn.ipynb b/modelcenter/community/google/t5-small-lm-adapt/introduction_cn.ipynb
index 641edd7a..01dac05e 100644
--- a/modelcenter/community/google/t5-small-lm-adapt/introduction_cn.ipynb
+++ b/modelcenter/community/google/t5-small-lm-adapt/introduction_cn.ipynb
@@ -74,7 +74,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-small-lm-adapt\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-small-lm-adapt/introduction_en.ipynb b/modelcenter/community/google/t5-small-lm-adapt/introduction_en.ipynb
index 21c1e824..d4ed2c5a 100644
--- a/modelcenter/community/google/t5-small-lm-adapt/introduction_en.ipynb
+++ b/modelcenter/community/google/t5-small-lm-adapt/introduction_en.ipynb
@@ -74,7 +74,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-small-lm-adapt\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-v1_1-base/introduction_cn.ipynb b/modelcenter/community/google/t5-v1_1-base/introduction_cn.ipynb
index fb4d969a..c8018971 100644
--- a/modelcenter/community/google/t5-v1_1-base/introduction_cn.ipynb
+++ b/modelcenter/community/google/t5-v1_1-base/introduction_cn.ipynb
@@ -65,7 +65,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-v1_1-base\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-v1_1-base/introduction_en.ipynb b/modelcenter/community/google/t5-v1_1-base/introduction_en.ipynb
index 4084d70f..efd5de43 100644
--- a/modelcenter/community/google/t5-v1_1-base/introduction_en.ipynb
+++ b/modelcenter/community/google/t5-v1_1-base/introduction_en.ipynb
@@ -65,7 +65,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-v1_1-base\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-v1_1-large/introduction_cn.ipynb b/modelcenter/community/google/t5-v1_1-large/introduction_cn.ipynb
index 1ad787e7..06ece433 100644
--- a/modelcenter/community/google/t5-v1_1-large/introduction_cn.ipynb
+++ b/modelcenter/community/google/t5-v1_1-large/introduction_cn.ipynb
@@ -65,7 +65,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-v1_1-large\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-v1_1-large/introduction_en.ipynb b/modelcenter/community/google/t5-v1_1-large/introduction_en.ipynb
index 4efcfb2f..8cf2ec83 100644
--- a/modelcenter/community/google/t5-v1_1-large/introduction_en.ipynb
+++ b/modelcenter/community/google/t5-v1_1-large/introduction_en.ipynb
@@ -65,7 +65,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-v1_1-large\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-v1_1-small/introduction_cn.ipynb b/modelcenter/community/google/t5-v1_1-small/introduction_cn.ipynb
index ebcc34ea..68386d8f 100644
--- a/modelcenter/community/google/t5-v1_1-small/introduction_cn.ipynb
+++ b/modelcenter/community/google/t5-v1_1-small/introduction_cn.ipynb
@@ -67,7 +67,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-v1_1-small\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
diff --git a/modelcenter/community/google/t5-v1_1-small/introduction_en.ipynb b/modelcenter/community/google/t5-v1_1-small/introduction_en.ipynb
index e89ecb34..a7eb5dc0 100644
--- a/modelcenter/community/google/t5-v1_1-small/introduction_en.ipynb
+++ b/modelcenter/community/google/t5-v1_1-small/introduction_en.ipynb
@@ -67,7 +67,8 @@
     "\n",
     "model = AutoModel.from_pretrained(\"google/t5-v1_1-small\")\n",
     "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
-    "print(model(input_ids))"
+    "decoder_input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
+    "print(model(input_ids, decoder_input_ids=decoder_input_ids))"
    ]
   },
   {
-- 
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