Merge pull request jina-ai#1 from hanxiao/master

update from base
mdoulaty · Sep 20, 2019 · bc572d0 · bc572d0
2 parents e768ac5 + 0ab546a
commit bc572d0
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diff --git a/client/README.md b/client/README.md
@@ -16,9 +16,8 @@
       <img src="https://readthedocs.org/projects/bert-as-service/badge/?version=latest"
            alt="ReadTheDoc">
     </a>
-  <a href="https://github.com/hanxiao/bert-as-service/releases">
-      <img src="https://img.shields.io/github/release/hanxiao/bert-as-service.svg"
-           alt="GitHub release">
+  <a href="https://pypi.org/search/?q=bert-serving">
+      <img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/bert-serving-server">
   </a>
   <a href="https://github.com/hanxiao/bert-as-service/issues">
         <img src="https://img.shields.io/github/issues/hanxiao/bert-as-service.svg"
@@ -53,6 +52,20 @@
 <h6 align="center">Made by Han Xiao • :globe_with_meridians: <a href="https://hanxiao.github.io">https://hanxiao.github.io</a></h6>
 
 
+<center>
+<table>
+  <tr>
+  <td width="25%"><a href="https://github.com/gnes-ai/gnes">
+      <img src=".github/gnes-logo-tight.svg" alt="GNES is Generic Neural Elastic Search (logo made by Han Xiao)">
+      </a></td>
+  <td>
+  <b>✨Looking for X-as-service? Or more generic and cloud-native solution?</b>
+  <p><br>Checkout my new project <a href="https://github.com/gnes-ai/gnes">GNES</a>! GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network. GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form.</p>
+</td>
+  </tr>
+</table>
+</center>
+
 <h2 align="center">What is it</h2>
 
 **BERT** is a NLP model [developed by Google](https://github.com/google-research/bert) for pre-training language representations. It leverages an enormous amount of plain text data publicly available on the web and is trained in an unsupervised manner. Pre-training a BERT model is a fairly expensive yet one-time procedure for each language. Fortunately, Google released several pre-trained models where [you can download from here](https://github.com/google-research/bert#pre-trained-models).

diff --git a/client/bert_serving/client/__init__.py b/client/bert_serving/client/__init__.py
@@ -17,7 +17,7 @@
 __all__ = ['__version__', 'BertClient', 'ConcurrentBertClient']
 
 # in the future client version must match with server version
-__version__ = '1.9.5'
+__version__ = '1.9.7'
 
 if sys.version_info >= (3, 0):
     from ._py3_var import *

diff --git a/server/README.md b/server/README.md
@@ -16,9 +16,8 @@
       <img src="https://readthedocs.org/projects/bert-as-service/badge/?version=latest"
            alt="ReadTheDoc">
     </a>
-  <a href="https://github.com/hanxiao/bert-as-service/releases">
-      <img src="https://img.shields.io/github/release/hanxiao/bert-as-service.svg"
-           alt="GitHub release">
+  <a href="https://pypi.org/search/?q=bert-serving">
+      <img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/bert-serving-server">
   </a>
   <a href="https://github.com/hanxiao/bert-as-service/issues">
         <img src="https://img.shields.io/github/issues/hanxiao/bert-as-service.svg"
@@ -53,6 +52,20 @@
 <h6 align="center">Made by Han Xiao • :globe_with_meridians: <a href="https://hanxiao.github.io">https://hanxiao.github.io</a></h6>
 
 
+<center>
+<table>
+  <tr>
+  <td width="25%"><a href="https://github.com/gnes-ai/gnes">
+      <img src=".github/gnes-logo-tight.svg" alt="GNES is Generic Neural Elastic Search (logo made by Han Xiao)">
+      </a></td>
+  <td>
+  <b>✨Looking for X-as-service? Or more generic and cloud-native solution?</b>
+  <p><br>Checkout my new project <a href="https://github.com/gnes-ai/gnes">GNES</a>! GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network. GNES enables large-scale index and semantic search for text-to-text, image-to-image, video-to-video and any-to-any content form.</p>
+</td>
+  </tr>
+</table>
+</center>
+
 <h2 align="center">What is it</h2>
 
 **BERT** is a NLP model [developed by Google](https://github.com/google-research/bert) for pre-training language representations. It leverages an enormous amount of plain text data publicly available on the web and is trained in an unsupervised manner. Pre-training a BERT model is a fairly expensive yet one-time procedure for each language. Fortunately, Google released several pre-trained models where [you can download from here](https://github.com/google-research/bert#pre-trained-models).

diff --git a/server/bert_serving/server/__init__.py b/server/bert_serving/server/__init__.py
@@ -24,7 +24,7 @@
 from .zmq_decor import multi_socket
 
 __all__ = ['__version__', 'BertServer']
-__version__ = '1.9.5'
+__version__ = '1.9.7'
 
 _tf_ver_ = check_tf_version()