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Intel on Hugging Face

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

Get started with deploying Intel's models on Intel® architecture with these hands-on tutorials from blogs written by engineers from Hugging Face and Intel:

Blog Description
Building Cost-Efficient Enterprise RAG applications with Intel Gaudi 2 and Intel Xeon Develop and deploy RAG applications as part of OPEA, the Open Platform for Enterprise AI
Running Large Multimodal Models on an AI PC's NPU Run the llava-gemma-2b model on an AI PC's NPU
A Chatbot on your Laptop: Phi-2 on Intel Meteor Lake Deploy Phi-2 on your local laptop with Intel OpenVINO in the Optimum Intel library

Get started on Intel architecture with Optimum Intel and Optimum Habana

To get started with Hugging Face Transformers software on Intel, visit the resources listed below.

Optimum Intel - To deploy on Intel® Xeon, Intel® Max Series GPU, and Intel® Core Ultra, check out optimum-intel, the interface between Intel architectures and the 🤗 Transformers and Diffusers libraries. You can use these backends:

Backend Installation
OpenVINO™ pip install --upgrade --upgrade-strategy eager "optimum[openvino]"
Intel® Extension for PyTorch* pip install --upgrade --upgrade-strategy eager "optimum[ipex]"
Intel® Neural Compressor pip install --upgrade --upgrade-strategy eager "optimum[neural-compressor]"

Optimum Habana - To deploy on Intel® Gaudi® AI accelerators, check out optimum-habana, the interface between Gaudi and the 🤗 Transformers and Diffusers libraries. To install the latest stable release:

pip install --upgrade-strategy eager optimum[habana]

Ways to get involved

Check out the Intel® Tiber™ AI Cloud to run your latest GenAI or LLM workload on Intel architecture.

Want to share your model fine-tuned on Intel architecture? And for more detailed deployment tips and sample code, please visit the "Deployment Tips" tab from the Powered-by-Intel LLM Leaderboard.

Join us on the Intel DevHub Discord to ask questions and interact with our AI developer community.