2 Ways to Setup Hugging Face Transformers Library (Python)

The quickest and easiest way to get started with Hugging Face Transformers Library is by making use of Google Colab, what's wonderful about Colab is that it allows us to use accelerating hardware, like GPUs or TPUs for free (smaller workloads).

Option 1: Google Colab

1. Open a Notebook in Colab.
2. Install the transformer library by in the cell of the notebook.

   !pip install transformers

Logs:

Requirement already satisfied:
 transformers in /usr/local/lib/python3.10/dist-packages (4.44.2)
 filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.16.1)
 huggingface-hub<1.0,>=0.23.2 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.24.7)
 numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.26.4)
 packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (24.1)
 pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.2)
 regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2024.9.11)
 requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.32.3)
 safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.5)
 tokenizers<0.20,>=0.19 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.19.1)
 tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.5)
 fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (2024.6.1)
 typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.2->transformers) (4.12.2)
 charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)
 idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.10)
 urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.2.3)
 certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2024.8.30

3. Check if the library is correctly installed by running,

   import transformers

Option 2: Using a Python Virtual Environment

• Step 1:Make sure you have an installed version of Python on your system.

  python3 --version
  Python 3.9.6

  or try,

  python --version
  Python 3.9.6

• Step 2: Create a project directory.

  mkdir ~/hugginface-transformers
  cd ~/hugginface-transformers

• Step 3: Create a virtual environment.

  python -m venv .env

• Step 4: Activate the virtual environment:

  For macOS and Linux:

  source .env/bin/activate

  For Windows:

  .env\Scripts\activate

• Step 5: Verify activation:

  For macOS and Linux

  which python

  For Windows

  where python

• Step 6: Installing transformer dependencies

  pip install transformers

Finally do not forget to check that the installation was correct by doing a basic sentiment analysis.

from transformers import pipeline

classifier = pipeline("sentiment-analysis")
classifier("I Love Code2care!")