#
Installation

Before you start, you’ll need to setup your environment and install the appropriate packages. `timm` is tested on Python 3+.

##
Virtual Environment

You should install `timm` in a virtual environment to keep things tidy and avoid dependency conflicts.

1. Create and navigate to your project directory:

       mkdir ~/my-project
       cd ~/my-project

2. Start a virtual environment inside your directory:

       python -m venv .env

3. Activate and deactivate the virtual environment with the following commands:

       # Activate the virtual environment
       source .env/bin/activate

       # Deactivate the virtual environment
       source .env/bin/deactivate

Once you’ve created your virtual environment, you can install `timm` in it.

##
Using pip

The most straightforward way to install `timm` is with pip:

    pip install timm

Alternatively, you can install `timm` from GitHub directly to get the latest, bleeding-edge version:

    pip install git+https://github.com/rwightman/pytorch-image-models.git

Run the following command to check if `timm` has been properly installed:

    python -c "from timm import list_models; print(list_models(pretrained=True)[:5])"

This command lists the first five pretrained models available in `timm` (which are sorted alphebetically). You should see the following output:

    ['adv_inception_v3', 'bat_resnext26ts', 'beit_base_patch16_224', 'beit_base_patch16_224_in22k', 'beit_base_patch16_384']

##
From Source

Building `timm` from source lets you make changes to the code base. To install from the source, clone the repository and install with the following commands:

    git clone https://github.com/rwightman/pytorch-image-models.git
    cd pytorch-image-models
    pip install -e .

Again, you can check if `timm` was properly installed with the following command:

    python -c "from timm import list_models; print(list_models(pretrained=True)[:5])"

Update on GitHub