--- title: README emoji: šŸ¢ colorFrom: purple colorTo: gray sdk: static pinned: false ---

Intel and Hugging Face are building powerful optimization tools to accelerate training and inference with Transformers.

Learn more about Hugging Face collaboration with Intel AI
Quantize Transformers with IntelĀ® Neural Compressor and Optimum
Quantizing 7B LLM on Intel CPU

Intel optimizes the most widely adopted and innovative AI software tools, frameworks, and libraries for IntelĀ® architecture. Whether you are computing locally or deploying AI applications on a massive scale, your organization can achieve peak performance with AI software optimized for IntelĀ® XeonĀ® Scalable platforms.

Intelā€™s engineering collaboration with Hugging Face offers state-of-the-art hardware and software acceleration to train, fine-tune and predict with Transformers.

Useful Resources:

To get started with IntelĀ® hardware and software optimizations, download and install the Optimum-IntelĀ® and IntelĀ® Extension for Transformers libraries with the following commands:


        $ python -m pip install "optimum-intel[extras]"@git+https://github.com/huggingface/optimum-intel.git
        $ python -m pip install intel-extension-for-transformers
      

For additional information on these two libraries including installation, features, and usage, see the two links below.

Next, find your desired model (and dataset) by searching in the search box at the top-left of Hugging Faceā€™s website. Add ā€œintelā€ to your search to narrow your search to IntelĀ®-pretrained models.

On the modelā€™s page (called a ā€œModel Cardā€) you will find description and usage information, an embedded inferencing demo, and the associated dataset. In the upper-right of your screen, click ā€œUse in Transformersā€ for helpful code hints on how to import the model to your own workspace with an established Hugging Face pipeline and tokenizer.

Library Source and Documentation: