Visual Language Models (VLMs) combine computer vision with natural language processing, enabling complex tasks such as image captioning and visual question…
As AI Agent applications become increasingly widespread, running large language models (LLMs) efficiently on personal computers (such as AI PCs powered by…
This article provides a detailed look at how to use Hugging Face's `optimum-intel` library and Intel's OpenVINO GenAI toolkit to optimize and deploy generative…
SetFit (Sentence Transformer Fine-Tuning) is a few-shot text classification framework co-developed by Hugging Face, Intel Labs, and other organizations. Rather…
This technical blog post from Hugging Face details how to locally deploy and run Microsoft's lightweight Phi-2 language model (2.7 billion parameters) on a…
When building Retrieval-Augmented Generation (RAG) systems, converting large volumes of text into embeddings (vectors) is an indispensable and computationally…
In the current boom of generative AI, image generation models like Stable Diffusion have become widely popular thanks to their remarkable capabilities…
This technical blog post from Hugging Face provides a detailed guide on optimizing and accelerating Stable Diffusion model inference on Intel CPUs…
Intel and Hugging Face announced a significant long-term partnership aimed at making machine learning hardware acceleration accessible to developers worldwide…