Merge pull request #11 from splovyt/update_readme_and_assets

Update README and make the assets and samples split

README.md

@@ -1,13 +1,15 @@
 [![Build Status](https://travis-ci.com/IBM/MAX-Text-Sentiment-Classifier.svg?branch=master)](https://travis-ci.com/IBM/MAX-Text-Sentiment-Classifier) [![API demo](https://img.shields.io/website/http/max-text-sentiment-classifier.max.us-south.containers.appdomain.cloud/swagger.json.svg?label=API%20demo&down_message=down&up_message=up)](http://max-text-sentiment-classifier.max.us-south.containers.appdomain.cloud/)
 
+[<img src="docs/deploy-max-to-ibm-cloud-with-kubernetes-button.png" width="400px">](http://ibm.biz/max-to-ibm-cloud-tutorial)
+
 # IBM Developer Model Asset Exchange: Text Sentiment Classifier
 
 This repository contains code to instantiate and deploy a text sentiment classifier. This model is able to detect whether a text fragment leans towards a positive or a negative sentiment. Optimal input examples for this model are short strings (preferably a single sentence) with correct grammar, although not a requirement.
 
 The model is based on the [pre-trained BERT-Base, English Uncased](https://github.com/google-research/bert/blob/master/README.md) model and was finetuned on the [IBM Claim Stance Dataset](http://www.research.ibm.com/haifa/dept/vst/debating_data.shtml). The model files are hosted on
 [IBM Cloud Object Storage](http://max-assets.s3.us.cloud-object-storage.appdomain.cloud/max-text-sentiment-classifier/1.0/assets.tar.gz).
 The code in this repository deploys the model as a web service in a Docker container. This repository was developed
-as part of the [IBM Developer Model Asset Exchange](https://developer.ibm.com/exchanges/models/).
+as part of the [IBM Developer Model Asset Exchange](https://developer.ibm.com/exchanges/models/) and the public API is powered by [IBM Cloud](https://ibm.biz/Bdz2XM).
 
 ## Model Metadata
 | Domain | Application | Industry  | Framework | Training Data | Input Data |
@@ -74,6 +76,8 @@ $ kubectl apply -f https://github.com/IBM/MAX-Text-Sentiment-Classifier/raw/mast
 
 The model will be available internally at port `5000`, but can also be accessed externally through the `NodePort`.
 
+A more elaborate tutorial on how to deploy this MAX model to production on [IBM Cloud](https://ibm.biz/Bdz2XM) can be found [here](http://ibm.biz/max-to-ibm-cloud-tutorial).
+
 ## Run Locally
 1. [Build the Model](#1-build-the-model)
 2. [Deploy the Model](#2-deploy-the-model)

samples/README.md

@@ -0,0 +1,5 @@
+# Sample Details
+
+## Test Examples
+
+The tab-separated-values file `test-examples.tsv` in the `samples` folder contains a fraction of the [IBM Claim Stance Dataset](http://www.research.ibm.com/haifa/dept/vst/debating_data.shtml#Claim%20Stance) ([CC-BY-SA](http://creativecommons.org/licenses/by-sa/3.0/)) not used for fine-tuning. In the first column, the claim is listed. In the second column, the corresponding sentiment (`pos` or `neg`) is listed. Claims in this file may be used to try out and benchmark the performance of this model.