How to Download from Hugging Face

How to Download from Hugging Face

Written by: Ameerah

Finding the right resources, especially pre-trained models and datasets, can be a major roadblock in the exciting world of machine learning. You spend hours scouring the internet, unsure which models are compatible, where to find reliable datasets, and how to download them efficiently.

Don’t let the hunt for models and datasets stall your project. This guide unlocks the secrets of how to download from Hugging Face, the treasure trove of pre-trained models and diverse datasets. Get ready to fuel your AI projects with ease!

Hugging Face: The Platform for Open-Source AI Collaboration

Hugging Face, primarily known as the platform, is an open-source hub that serves as a central meeting ground for the machine learning (ML) community, particularly focusing on natural language processing (NLP).

Here are the key aspects of the platform:

1. Sharing and Accessing Resources:

  • Models: Hugging Face boasts a vast library containing over 250,000 pre-trained models covering various NLP tasks like text generation, translation, and question answering.
  • Datasets: Users can access and utilize a diverse collection of datasets for training and evaluating their models.
  • Code: The platform encourages sharing code for building and deploying models, facilitating collaboration and learning from each other.

2. Training and Deployment:

  • Infrastructure: Hugging Face offers managed infrastructure for users to train their own custom models with varying complexities.
  • Deployment Tools: The platform provides tools and resources to deploy trained models into production environments, allowing users to put their models into real-world applications.

3. Collaboration and Community:

  • Version Control: Similar to GitHub, Hugging Face utilizes a version control system for models and datasets, allowing users to track changes and collaborate effectively.
  • Discussions and Forums: The platform fosters discussions and forums where users can share ideas, ask questions, and learn from other members of the community.

Benefits Of Hugging Face

  • Reduced development time: Access to pre-trained models and datasets saves users significant time and effort compared to building everything from scratch.
  • Enhanced innovation: The collaborative nature of the platform fosters sharing and development of new and improved models and techniques, leading to faster advancements in the field.
  • Democratization of AI: Hugging Face provides a user-friendly platform for anyone, regardless of their technical expertise, to explore and experiment with AI, making this powerful technology more accessible.
  • Improved model performance: Users can leverage pre-trained models as a starting point for fine-tuning, often leading to better performance on specific tasks compared to building a model from scratch.
  • Facilitates collaboration: Version control and discussion forums enable smooth collaboration between researchers and developers, promoting knowledge sharing and joint efforts in pushing the boundaries of AI.
  • Reduced computational resources: Utilizing pre-trained models can significantly reduce the computational resources required for projects, making AI development more accessible to individuals and smaller organizations.

Hugging Face

How to Download from Hugging Face

There are two main ways how to download models from Hugging Face:

1. Using the Hugging Face Client Library (huggingface_hub):

This method is ideal for programmatic access within your Python code. Here’s a summary:

  • Install the library:

    pip install huggingface_hub

  • Import the library:

    from huggingface_hub import hf_hub_download

  • Use the  function:


    Hugging face

2. Through the Hugging Face Website:

If you prefer a web-based approach:

  1. Navigate to the desired model or dataset page on hugging face website
  2. Locate the “Files & Versions” section.
  3. Click on the download icon next to the file you want to download.

How to Download Dataset from Hugging Face

Downloading datasets from Hugging Face involves two main approaches:

1. Using the Hugging Face Client Library (huggingface_hub)

This method is ideal for programmatic access within your Python code and offers granular control over the download process:

a. Install the library:

pip install huggingface_hub

b. Import the library and use


how to download dataset from hugging face


By now, you should be equipped with the knowledge how to download from Hugging Face (models and datasets)  using both the user-friendly website interface and the programmatic approach through the huggingface_hub library. Choosing the appropriate method depends on your project requirements and technical preferences. Whichever method you choose, downloading resources from Hugging Face opens a world of possibilities for experimentation, innovation, and advancement in the field of machine learning.


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