diff --git a/docs/source/api/maas_lib.pipelines.audio.rst b/docs/source/api/maas_lib.pipelines.audio.rst
new file mode 100644
index 00000000..71e29b42
--- /dev/null
+++ b/docs/source/api/maas_lib.pipelines.audio.rst
@@ -0,0 +1,7 @@
+maas\_lib.pipelines.audio package
+=================================
+
+.. automodule:: maas_lib.pipelines.audio
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/docs/source/api/maas_lib.trainers.nlp.rst b/docs/source/api/maas_lib.trainers.nlp.rst
new file mode 100644
index 00000000..71f484ca
--- /dev/null
+++ b/docs/source/api/maas_lib.trainers.nlp.rst
@@ -0,0 +1,18 @@
+maas\_lib.trainers.nlp package
+==============================
+
+.. automodule:: maas_lib.trainers.nlp
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Submodules
+----------
+
+maas\_lib.trainers.nlp.sequence\_classification\_trainer module
+---------------------------------------------------------------
+
+.. automodule:: maas_lib.trainers.nlp.sequence_classification_trainer
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/docs/source/api/maas_lib.trainers.rst b/docs/source/api/maas_lib.trainers.rst
new file mode 100644
index 00000000..eb90ee4f
--- /dev/null
+++ b/docs/source/api/maas_lib.trainers.rst
@@ -0,0 +1,34 @@
+maas\_lib.trainers package
+==========================
+
+.. automodule:: maas_lib.trainers
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+Subpackages
+-----------
+
+.. toctree::
+   :maxdepth: 4
+
+   maas_lib.trainers.nlp
+
+Submodules
+----------
+
+maas\_lib.trainers.base module
+------------------------------
+
+.. automodule:: maas_lib.trainers.base
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+maas\_lib.trainers.builder module
+---------------------------------
+
+.. automodule:: maas_lib.trainers.builder
+   :members:
+   :undoc-members:
+   :show-inheritance:
diff --git a/docs/source/faq.md b/docs/source/faq.md
new file mode 100644
index 00000000..a93fafdc
--- /dev/null
+++ b/docs/source/faq.md
@@ -0,0 +1,31 @@
+# 常见问题
+
+<a name="macos-pip-tokenizer-error"></a>
+
+### 1. macOS环境pip方式安装tokenizers报错
+
+对于tokenizers库， pypi上缺乏针对`macOS`环境预编译包，需要搭建源码编译环境后才能正确安装，步骤如下：
+
+1. 安装rust
+    ```shell
+    curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
+    pip install setuptools_rust
+
+    ```
+
+2. 更新rust环境变量
+
+    ```shell
+    source $HOME/.cargo/env
+    ```
+3. 安装tokenziers
+    ```shell
+    pip install tokenziers
+    ```
+reference: [https://huggingface.co/docs/tokenizers/installation#installation-from-sources](https://huggingface.co/docs/tokenizers/installation#installation-from-sources)
+
+### 2. pip 安装包冲突
+
+> ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
+
+由于依赖库之间的版本不兼容，可能会存在版本冲突的情况，大部分情况下不影响正常运行。
diff --git a/docs/source/quick_start.md b/docs/source/quick_start.md
index 3b483081..de5f8da8 100644
--- a/docs/source/quick_start.md
+++ b/docs/source/quick_start.md
@@ -1,17 +1,53 @@
 # 快速开始
 
-## 环境准备
+## python环境配置
+首先，参考[文档](https://docs.anaconda.com/anaconda/install/) 安装配置Anaconda环境
 
-方式一： whl包安装， 执行如下命令
+安装完成后，执行如下命令为maas library创建对应的python环境。
 ```shell
-pip install http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas_lib-0.1.0-py3-none-any.whl
+conda create -n maas python=3.6
+conda activate maas
 ```
+检查python和pip命令是否切换到conda环境下。
+```shell
+which python
+# ~/workspace/anaconda3/envs/maas/bin/python
+
+which pip
+# ~/workspace/anaconda3/envs/maas/bin/pip
+```
+注： 本项目只支持`python3`环境，请勿使用python2环境。
+
+## 第三方依赖安装
+
+MaaS Library支持tensorflow，pytorch两大深度学习框架进行模型训练、推理， 在Python 3.6+,  Pytorch 1.8+, Tensorflow 2.6上测试可运行，用户可以根据所选模型对应的计算框架进行安装，可以参考如下链接进行安装所需框架:
+
+* [Pytorch安装指导](https://pytorch.org/get-started/locally/)
+* [Tensorflow安装指导](https://www.tensorflow.org/install/pip)
+
 
-方式二： 源码环境指定， 适合本地开发调试使用，修改源码后可以直接执行
+## MaaS library 安装
+
+注： 如果在安装过程中遇到错误，请前往[常见问题](faq.md)查找解决方案。
+
+### pip安装
+```shell
+pip install -r http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/maas.txt
+```
+
+安装成功后，可以执行如下命令进行验证安装是否正确
+```shell
+python -c "from maas_lib.pipelines import pipeline;print(pipeline('image-matting',model='damo/image-matting-person')('http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/data/test/maas/image_matting/test.png'))"
+```
+
+
+### 使用源码
+
+适合本地开发调试使用，修改源码后可以直接执行
 ```shell
 git clone git@gitlab.alibaba-inc.com:Ali-MaaS/MaaS-lib.git maaslib
-git fetch origin release/0.1
-git checkout release/0.1
+git fetch origin master
+git checkout master
 
 cd maaslib
 
@@ -22,7 +58,11 @@ pip install -r requirements.txt
 export PYTHONPATH=`pwd`
 ```
 
-备注： mac arm cpu暂时由于依赖包版本问题会导致requirements暂时无法安装，请使用mac intel cpu， linux cpu/gpu机器测试。
+安装成功后，可以执行如下命令进行验证安装是否正确
+```shell
+python -c "from maas_lib.pipelines import pipeline;print(pipeline('image-matting',model='damo/image-matting-person')('http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/data/test/maas/image_matting/test.png'))"
+```
+
 
 
 ## 训练
@@ -34,31 +74,22 @@ to be done
 to be done
 
 ## 推理
-to be done
-<!-- pipeline函数提供了简洁的推理接口，示例如下
 
-注： 这里提供的接口是完成和modelhub打通后的接口，暂时不支持使用。pipeline使用示例请参考 [pipelien tutorial](tutorials/pipeline.md)给出的示例。
+pipeline函数提供了简洁的推理接口，示例如下， 更多pipeline介绍和示例请参考[pipeline使用教程](tutorials/pipeline.md)
 
 ```python
 import cv2
+import os.path as osp
 from maas_lib.pipelines import pipeline
+from maas_lib.utils.constant import Tasks
 
 # 根据任务名创建pipeline
-img_matting = pipeline('image-matting')
-
-# 根据任务和模型名创建pipeline
-img_matting = pipeline('image-matting', model='damo/image-matting-person')
+img_matting = pipeline(
+    Tasks.image_matting, model='damo/image-matting-person')
 
-# 自定义模型和预处理创建pipeline
-model = Model.from_pretrained('damo/xxx')
-preprocessor = Preprocessor.from_pretrained(cfg)
-img_matting = pipeline('image-matting', model=model, preprocessor=preprocessor)
-
-# 推理
 result = img_matting(
-                'http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/data/test/maas/image_matting/test.png'
-            )
-
-# 保存结果图片
+    'http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/data/test/maas/image_matting/test.png'
+)
 cv2.imwrite('result.png', result['output_png'])
-``` -->
+print(f'result file path is {osp.abspath("result.png")}')
+```
diff --git a/docs/source/tutorials/pipeline.md b/docs/source/tutorials/pipeline.md
index ad73c773..a91d15bd 100644
--- a/docs/source/tutorials/pipeline.md
+++ b/docs/source/tutorials/pipeline.md
@@ -27,7 +27,7 @@
    执行如下python代码
    ```python
    >>> from maas_lib.pipelines import pipeline
-   >>> img_matting = pipeline(task='image-matting', model_path='matting_person.pb')
+   >>> img_matting = pipeline(task='image-matting', model='damo/image-matting-person')
    ```
 
 2. 传入单张图像url进行处理
@@ -35,6 +35,8 @@
    >>> import cv2
    >>> result = img_matting('http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/data/test/maas/image_matting/test.png')
    >>> cv2.imwrite('result.png', result['output_png'])
+   >>> import os.path as osp
+   >>> print(f'result file path is {osp.abspath("result.png")}')
    ```
 
    pipeline对象也支持传入一个列表输入，返回对应输出列表，每个元素对应输入样本的返回结果
@@ -57,10 +59,12 @@
 pipeline函数支持传入实例化的预处理对象、模型对象，从而支持用户在推理过程中定制化预处理、模型。
 下面以文本情感分类为例进行介绍。
 
+由于demo模型为EasyNLP提供的模型，首先，安装EasyNLP
+```shell
+pip install https://atp-modelzoo-sh.oss-cn-shanghai.aliyuncs.com/release/package/whl/easynlp-0.0.4-py2.py3-none-any.whl
+```
 
 
-注： 当前release版本还未实现AutoModel的语法糖，需要手动实例化模型，后续会加上对应语法糖简化调用
-
 下载模型文件
 ```shell
 wget https://atp-modelzoo-sh.oss-cn-shanghai.aliyuncs.com/release/easynlp_modelzoo/alibaba-pai/bert-base-sst2.zip && unzip bert-base-sst2.zip
@@ -68,18 +72,17 @@ wget https://atp-modelzoo-sh.oss-cn-shanghai.aliyuncs.com/release/easynlp_modelz
 
 创建tokenizer和模型
 ```python
->>> from maas_lib.models.nlp import SequenceClassificationModel
->>> path = 'bert-base-sst2'
->>> model = SequenceClassificationModel(path)
+>>> from maas_lib.models import Model
 >>> from maas_lib.preprocessors import SequenceClassificationPreprocessor
+>>> model = Model.from_pretrained('damo/bert-base-sst2')
 >>> tokenizer = SequenceClassificationPreprocessor(
-                path, first_sequence='sentence', second_sequence=None)
+            model.model_dir, first_sequence='sentence', second_sequence=None)
 ```
 
 使用tokenizer和模型对象创建pipeline
 ```python
 >>> from maas_lib.pipelines import pipeline
->>> semantic_cls = pipeline('text-classification', model=model, preprocessor=tokenizer)
+>>> semantic_cls = pipeline('text-classification', model=model,   preprocessor=tokenizer)
 >>> semantic_cls("Hello world!")
 ```
 
diff --git a/maas_lib/models/__init__.py b/maas_lib/models/__init__.py
index f1ba8980..aa1b3f14 100644
--- a/maas_lib/models/__init__.py
+++ b/maas_lib/models/__init__.py
@@ -2,3 +2,4 @@
 
 from .base import Model
 from .builder import MODELS, build_model
+from .nlp import SequenceClassificationModel
diff --git a/maas_lib/models/nlp/sequence_classification_model.py b/maas_lib/models/nlp/sequence_classification_model.py
index dbb86105..d29587a0 100644
--- a/maas_lib/models/nlp/sequence_classification_model.py
+++ b/maas_lib/models/nlp/sequence_classification_model.py
@@ -1,7 +1,6 @@
 from typing import Any, Dict, Optional, Union
 
 import numpy as np
-import torch
 
 from maas_lib.utils.constant import Tasks
 from ..base import Model
@@ -26,6 +25,7 @@ class SequenceClassificationModel(Model):
         super().__init__(model_dir, *args, **kwargs)
         from easynlp.appzoo import SequenceClassification
         from easynlp.core.predictor import get_model_predictor
+        import torch
         self.model = get_model_predictor(
             model_dir=self.model_dir,
             model_cls=SequenceClassification,
diff --git a/maas_lib/pipelines/cv/image_matting.py b/maas_lib/pipelines/cv/image_matting.py
index 73796552..fdb443f9 100644
--- a/maas_lib/pipelines/cv/image_matting.py
+++ b/maas_lib/pipelines/cv/image_matting.py
@@ -4,7 +4,6 @@ from typing import Any, Dict, List, Tuple, Union
 import cv2
 import numpy as np
 import PIL
-import tensorflow as tf
 from cv2 import COLOR_GRAY2RGB
 
 from maas_lib.pipelines.base import Input
@@ -14,9 +13,6 @@ from maas_lib.utils.logger import get_logger
 from ..base import Pipeline
 from ..builder import PIPELINES
 
-if tf.__version__ >= '2.0':
-    tf = tf.compat.v1
-
 logger = get_logger()
 
 
@@ -26,6 +22,9 @@ class ImageMatting(Pipeline):
 
     def __init__(self, model: str):
         super().__init__(model=model)
+        import tensorflow as tf
+        if tf.__version__ >= '2.0':
+            tf = tf.compat.v1
         model_path = osp.join(self.model, 'matting_person.pb')
 
         config = tf.ConfigProto(allow_soft_placement=True)
diff --git a/maas_lib/version.py b/maas_lib/version.py
index b794fd40..df9144c5 100644
--- a/maas_lib/version.py
+++ b/maas_lib/version.py
@@ -1 +1 @@
-__version__ = '0.1.0'
+__version__ = '0.1.1'
diff --git a/requirements/maas.txt b/requirements/maas.txt
new file mode 100644
index 00000000..3b64c375
--- /dev/null
+++ b/requirements/maas.txt
@@ -0,0 +1,2 @@
+http://pai-vision-data-hz.oss-cn-zhangjiakou.aliyuncs.com/release/maas/maas_lib-0.1.1-py3-none-any.whl
+https://maashub.oss-cn-hangzhou.aliyuncs.com/releases/maas_hub-0.1.0.dev0-py2.py3-none-any.whl
diff --git a/requirements/pipeline.txt b/requirements/pipeline.txt
index 259bbb1b..64500a6b 100644
--- a/requirements/pipeline.txt
+++ b/requirements/pipeline.txt
@@ -1,6 +1,6 @@
 #https://atp-modelzoo-sh.oss-cn-shanghai.aliyuncs.com/release/package/whl/easynlp-0.0.4-py2.py3-none-any.whl
-tensorflow
+# tensorflow
 #--find-links https://download.pytorch.org/whl/torch_stable.html
-torch<1.10,>=1.8.0
-torchaudio
-torchvision
+# torch<1.10,>=1.8.0
+# torchaudio
+# torchvision
diff --git a/requirements/runtime.txt b/requirements/runtime.txt
index 303a084c..8f74e780 100644
--- a/requirements/runtime.txt
+++ b/requirements/runtime.txt
@@ -5,5 +5,6 @@ opencv-python-headless
 Pillow
 pyyaml
 requests
-transformers
+tokenizers<=0.10.3
+transformers<=4.16.2
 yapf