This technical blog post from Hugging Face introduces how to build a powerful and efficient speech processing system using Hugging Face Inference Endpoints — a…
When developing applications based on large language models (LLMs) — such as AI agents, RAG systems, or automated workflows — one of the biggest challenges…
### Background and Challenges In the field of code generation, instruction tuning is the key to improving a model's practical utility and alignment with human…
Hugging Face has announced the launch of the new "Open Chain of Thought (CoT) Leaderboard," a public platform specifically designed to evaluate and compare the…
Snowflake recently launched a brand-new open-source large language model called "Snowflake Arctic" — a Mixture of Experts (MoE) model designed for…
Hugging Face has announced the official launch of the "Open Medical-LLM Leaderboard" in collaboration with researchers from Open Life Science AI and the…
This case study details how biomedical AI startup Ryght leveraged Hugging Face's Expert Support service to overcome the many challenges of deploying generative…
As code large language models (Code LLMs) develop rapidly, fairly and accurately evaluating their capabilities has become a major challenge. Traditional…
Hugging Face has announced the launch of Idefics2, the next generation of its open-source Vision Language Model (VLM). With 8 billion (8B) parameters, this…
This technical blog post published by Hugging Face provides an accessible yet thorough breakdown of the core principles and applications of Vision Language…
Hugging Face and Google Cloud have announced a deep strategic partnership, officially integrating thousands of popular open-source large language models (LLMs)…
Google and Hugging Face have jointly announced the launch of CodeGemma, a family of lightweight open-source large language models (LLMs) designed specifically…
Hugging Face has officially published its core positions and commitments on Public Policy. As global debates over AI regulation intensify — from the EU's AI…
This tutorial article details how to build an efficient natural language to SQL (Text2SQL) query system using tools from the Hugging Face ecosystem and a…
Hugging Face and internet infrastructure giant Cloudflare have announced a major partnership that officially brings serverless GPU inference services to…
As RAG (Retrieval-Augmented Generation) and semantic search have become widespread, the maintenance costs of vector databases — especially RAM overhead — have…
This is a beginner's guide written by the official Hugging Face blog for "total noobs" with absolutely no machine learning background, aimed at demystifying…
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…
As the parameter counts of large language models (LLMs) have skyrocketed, the hardware requirements for training and fine-tuning these models have risen…
Hugging Face has announced a deep partnership with NVIDIA to directly integrate NVIDIA DGX Cloud services into the Hugging Face platform. This collaboration…
Hugging Face has officially introduced Quanto, a brand-new quantization library designed for PyTorch, which has been integrated as a backend into the Hugging…
The Hugging Face official blog has published a post introducing WebSight, a brand-new open-source dataset designed to address the bottleneck that multimodal…
When building Retrieval-Augmented Generation (RAG) systems, converting large volumes of text into embeddings (vectors) is an indispensable and computationally…
Hugging Face has announced the launch of a new multimodal benchmark and leaderboard called "ConTextual," aimed at addressing the shortcomings of existing…
### Background and Challenge: The High-Quality Data Bottleneck In the current development of generative AI and large language models (LLMs), the industry…
With the explosive growth of large language models (LLMs), the demand for high-performance, cost-effective AI hardware has increased significantly. Intel Gaudi…
The BigCode community, jointly led by Hugging Face and ServiceNow, together with NVIDIA, has officially announced the launch of a new generation of open-source…
This guide from Hugging Face systematically introduces the technical principles, categories, existing tools, and real-world challenges of AI watermarking. As…
This article provides an in-depth introduction to Matryoshka Representation Learning (MRL), also known as Matryoshka embedding models. Traditional embedding…
After Google released the Gemma family of open-source models (including 2B and 7B parameter versions), Hugging Face promptly published this practical…