README.md in torch-rb-0.5.3 vs README.md in torch-rb-0.6.0

@@ -28,11 +28,11 @@
 
 ## Getting Started
 
 Deep learning is significantly faster with a GPU. If you don’t have an NVIDIA GPU, we recommend using a cloud service. [Paperspace](https://www.paperspace.com/) has a great free plan.
 
-We’ve put together a [Docker image](https://github.com/ankane/ml-stack) to make it easy to get started. On Paperspace, create a notebook with a custom container. Set the container name to:
+We’ve put together a [Docker image](https://github.com/ankane/ml-stack) to make it easy to get started. On Paperspace, create a notebook with a custom container. Under advanced options, set the container name to:
 
 ```text
 ankane/ml-stack:torch-gpu
 ```
 
@@ -408,10 +408,11 @@
 
 - [Image classification with MNIST](examples/mnist) ([日本語版](https://qiita.com/kojix2/items/c19c36dc1bf73ea93409))
 - [Collaborative filtering with MovieLens](examples/movielens)
 - [Sequence models and word embeddings](examples/nlp)
 - [Generative adversarial networks](examples/gan)
+- [Transfer learning](examples/transfer-learning)
 
 ## LibTorch Installation
 
 [Download LibTorch](https://pytorch.org/). For Linux, use the `cxx11 ABI` version. Then run:
 
@@ -421,11 +422,12 @@
 
 Here’s the list of compatible versions.
 
 Torch.rb | LibTorch
 --- | ---
-0.5.0+ | 1.7.0-1.7.1
-0.3.0+ | 1.6.0
+0.6.0+ | 1.8.0+
+0.5.0-0.5.3 | 1.7.0-1.7.1
+0.3.0-0.4.2 | 1.6.0
 0.2.0-0.2.7 | 1.5.0-1.5.1
 0.1.8 | 1.4.0
 0.1.0-0.1.7 | 1.3.1
 
 ### Homebrew