update readme

README.md

@@ -1,15 +1,18 @@
-PyTorchNet
+TNT
 ==========
 
-PyTorch version of https://github.com/torchnet/torchnet
+**TNT** is a library providing powerful dataloading, logging and visualization utlities for Python.
+It is closely intergrated with [PyTorch](http://pytorch.org) and is designed to enable rapid iteration with any model 
+or training regimen.
 
-![travis](https://travis-ci.org/pytorch/tnt.svg?branch=master)
+![travis](https://travis-ci.org/pytorch/tnt.svg?branch=master) 
+[![Documentation Status](https://readthedocs.org/projects/tnt/badge/?version=latest)](http://tnt.readthedocs.io/en/latest/?badge=latest)
 
-_torchnet_ is a framework for torch which provides a set of abstractions aiming
-at encouraging code re-use as well as encouraging modular programming.
+- [About](#About)
+- [Installation](#Installation)
+- [Documentation](http://tnt.readthedocs.io)
+- [Getting Started](#Getting-Started)
 
-Most of the modules support NumPy arrays as well as PyTorch tensors on input,
-so could potentially be used with other frameworks.
 
 ## Installation
 
@@ -25,7 +28,30 @@ To update:
 pip install --upgrade git+https://github.com/pytorch/tnt.git@master
 ```
 
-## Differences with lua version
+## About
+TNT (imported as _torchnet_) is a framework for PyTorch which provides a set of abstractions for PyTorch 
+aiming at encouraging code re-use as well as encouraging modular programming. It provides powerful dataloading, logging,
+and visualization utilities. 
+
+The project was inspired by [TorchNet](https://github.com/torchnet/torchnet), and legend says that it stood for “TorchNetTwo”. 
+Since the deprecation of TorchNet TNT has developed on its own.
+
+For example, TNT provides simple methods to record model preformance in the `torchnet.meter` module and to log them to Visdom
+(or in the future, TensorboardX) with the `torchnet.logging` module.
+
+In the future, TNT will also provide strong support for multi-task learning and transfer learning applications. It 
+currently supports joint training data loading through torchnet.utils.MultiTaskDataLoader.
+
+Most of the modules support NumPy arrays as well as PyTorch tensors on input, and so could potentially be used with 
+other frameworks.
+
+
+## Getting Started
+See some of the examples in https://github.com/pytorch/examples. We would like to include some walkthroughs in the
+[docs](tnt.readthedocs.io) (contributions welcome!).
+
+
+## [LEGACY] Differences with lua version
 
 What's been ported so far: