The article explains how modern LLMs convert text into token IDs, embeddings, and position-aware vectors before passing them through stacked transformer blocks. It covers attention, multi-head attention, KV cache, GQA, feed-forward networks, MoE, residual streams, normalization, and decoding. Its goal is educational: helping readers understand the common architecture behind many current model families and read model cards or papers more confidently.
Hugging Face published a tutorial for running Reachy Mini conversations without cloud audio processing or API keys. The setup uses its speech-to-speech library as a cascaded VAD, STT, LLM, and TTS pipeline exposed through a Realtime API-compatible WebSocket. Recommended defaults include llama.cpp with Gemma 4, Silero VAD, Parakeet-TDT, and Qwen3-TTS, while allowing swaps to vLLM, MLX, Transformers, or hosted Responses API providers.
Hugging Face's official blog has announced that DeepInfra — a well-known high-performance, low-cost serverless inference platform — has officially joined…
Hugging Face has published its Spring 2026 "State of Open Source AI" report, offering a comprehensive review of the explosive growth and paradigm shifts that…
Mixture of Experts (MoE) has become the mainstream architecture for current large language models (LLMs). This article takes an in-depth look at how MoE…
Hugging Face's official blog has announced exciting news for the open-source AI community: Hugging Face has formed a deep partnership with Unsloth — the…
Hugging Face has announced a new partnership with OVHcloud, Europe's leading cloud infrastructure provider, officially incorporating OVHcloud into Hugging Face…
Hugging Face continues to expand its "Inference Providers" program, aimed at enabling developers to run open-source models from Hugging Face Hub in the…
Replicate has officially launched a remote MCP (Model Context Protocol) server. MCP is an open standard created by Anthropic that enables large language models…
Hugging Face has officially launched a new tool called "AI Sheets," an intuitive spreadsheet tool designed specifically for dataset processing. It aims to make…
Hugging Face and NVIDIA have announced a new collaboration to bring NVIDIA NIM (NVIDIA Inference Microservices) into the Hugging Face ecosystem, with the goal…
Hugging Face announced a deep partnership with Groq, a chip company focused on ultra-fast AI inference, formally bringing Groq into the Hugging Face "Inference…
As enterprises place ever-increasing demands on data privacy, security, and regulatory compliance, deploying AI models on-premises has become the preferred…
### Background and Pain Points: Moving Beyond the Overly Simple "Needle in a Haystack" Test In recent years, the context window length supported by large…
Hugging Face's "NLP Course" has long been a must-read classic for developers and researchers worldwide looking to enter the fields of Transformers and natural…
Hugging Face's official blog has announced that its widely adopted open-source large model inference framework, Text Generation Inference (TGI), now officially…
Hugging Face has officially launched the "Inference Providers" feature on the Hugging Face Hub — a major update designed to address the pain points developers…
This technical blog post from Hugging Face provides a detailed benchmark of running large language models (LLMs) on Google Cloud Platform's (GCP) new C4…
This educational article from Hugging Face aims to guide readers — in the most intuitive, step-by-step way — to "reinvent" RoPE (Rotary Position Embedding)…
This case study provides a detailed account of how non-profit organization Digital Green, with support from Hugging Face's Expert Support team, optimized its…
Hugging Face has officially launched HUGS (Hugging Face Microservices), a brand-new microservices solution designed to address the pain points enterprises face…
AMD has officially launched its 5th-generation EPYC processor, codenamed "Turin," and Hugging Face has promptly published a blog post detailing the deep…
Hugging Face has officially introduced the "Community Tools" feature to its open-source chat platform, HuggingChat. This major update injects powerful Agent…
### Background and Pain Points In AI agent development, "tool use" (also known as function calling) is the core capability that allows large language models…
Hugging Face and NVIDIA announced a major partnership in late July 2024, officially launching a serverless inference service powered by NVIDIA NIM (NVIDIA…
Following Apple's major Core ML updates announced at WWDC 24, Hugging Face published a practical guide detailing how to convert the popular open-source large…
The Hugging Face official blog has introduced a major update to its open-source text generation inference engine, Text Generation Inference (TGI): the…
Hugging Face officially announced a deep integration with KerasHub — the new unified library for natural language processing (NLP) and computer vision (CV) in…
### Background and Challenges France's Banque des Territoires (part of the Caisse des Dépôts et Consignations — CDC Group) is committed to promoting local…
Hugging Face has announced official support for AWS Inferentia2 (Inf2) instances within its hosted Inference Endpoints service. This update gives developers…