diff --git a/README.md b/README.md
index 4e47737a9..8f564f894 100644
--- a/README.md
+++ b/README.md
@@ -62,11 +62,14 @@ Choose the right framework for every part of a model's lifetime
 
 ## Installation
 
-This repo is tested on Python 2.7 and 3.5+ (examples are tested only on python 3.5+) and PyTorch 1.0.0+
+This repo is tested on Python 2.7 and 3.5+ (examples are tested only on python 3.5+), PyTorch 1.0.0+ and TensorFlow 2.0.0-rc1
 
 ### With pip
 
-Transformers can be installed by pip as follows:
+First you need to install one of, or both, TensorFlow 2.0 and PyTorch.
+Please refere to [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available) and/or [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform.
+
+When TensorFlow 2.0 and/or PyTorch has been installed, 🤗 Transformers can be installed using pip as follows:
 
 ```bash
 pip install transformers
@@ -74,7 +77,10 @@ pip install transformers
 
 ### From source
 
-Clone the repository and run:
+Here also, you first need to install one of, or both, TensorFlow 2.0 and PyTorch.
+Please refere to [TensorFlow installation page](https://www.tensorflow.org/install/pip#tensorflow-2.0-rc-is-available) and/or [PyTorch installation page](https://pytorch.org/get-started/locally/#start-locally) regarding the specific install command for your platform.
+
+When TensorFlow 2.0 and/or PyTorch has been installed, you can install from source by cloning the repository and runing:
 
 ```bash
 pip install [--editable] .
@@ -86,6 +92,8 @@ A series of tests is included for the library and the example scripts. Library t
 
 These tests can be run using `pytest` (install pytest if needed with `pip install pytest`).
 
+Depending on which framework is installed (TensorFlow 2.0 and/or PyTorch), the irrelevant tests will be skipped. Ensure that both frameworks are installed if you want to execute all tests.
+
 You can run the tests from the root of the cloned repository with the commands:
 
 ```bash
@@ -99,8 +107,7 @@ You should check out our [`swift-coreml-transformers`](https://github.com/huggin
 
 It contains an example of a conversion script from a Pytorch trained Transformer model (here, `GPT-2`) to a CoreML model that runs on iOS devices.
 
-At some point in the future, you'll be able to seamlessly move from pre-training or fine-tuning models in PyTorch to productizing them in CoreML,
-or prototype a model or an app in CoreML then research its hyperparameters or architecture from PyTorch. Super exciting!
+At some point in the future, you'll be able to seamlessly move from pre-training or fine-tuning models to productizing them in CoreML, or prototype a model or an app in CoreML then research its hyperparameters or architecture from TensorFlow 2.0 and/or PyTorch. Super exciting!
 
 ## Model architectures