diff --git a/README.md b/README.md index ffdd100e..a1a95f7f 100644 --- a/README.md +++ b/README.md @@ -112,11 +112,12 @@ We suggest testing the library on your AI models right away by following the ins There are two ways to install `nebullvm`: -1. Using PyPI. We suggest installing the library with `pip` to get the stable +- Step 1-A: Using PyPI. We suggest installing the library with `pip` to get the stable version of `nebullvm` -2. From source code to get the latest features + +- Step 1-B: From source code to get the latest features -#### Option 1A: Installation with PyPI (recommended) +#### Step 1-A: Installation with PyPI (recommended) The easiest way to install `nebullvm` is by using `pip`, running @@ -124,7 +125,7 @@ The easiest way to install `nebullvm` is by using `pip`, running pip install nebullvm ``` -#### Option 1B: Source code installation +#### Step 1-B: Source code installation To install the source code you have to clone the directory on your local machine using `git`. @@ -147,9 +148,9 @@ pip install . Now you need to install the compilers that the library leverages to create the optimized version of your models. We have built an auto-installer to install them -automatically. +automatically. We propose 3 options (2-A, 2-B and 2-C) to achieve this goal. -#### Option 2A: Installation at the first optimization run +#### Step 2-A: Installation at the first optimization run The auto-installer is activated after you import `nebullvm` and perform your first optimization. You may run into import errors related to the deep learning @@ -157,7 +158,7 @@ compiler installation, but you can ignore these errors/warnings. It is also recommended restarting the python kernel between the auto-installation and the first optimization, otherwise not all compilers will be activated. -#### Option B: Installation before the first optimization run (recommended) +#### Step 2-B: Installation before the first optimization run (recommended) To avoid any problems, we strongly recommend running the auto-installation before performing the first optimization by running @@ -169,7 +170,7 @@ python -c "import nebullvm" You should ignore at this stage any import warning resulting from the previous command. -#### Option 2C: Selective installation of deep learning compilers +#### Step 2-C: Selective installation of deep learning compilers The library automatically installs all deep learning compilers it supports. In case you would be interested in bypassing the automatic installation, you can export the environment variable `NO_COMPILER_INSTALLATION=1` by running