We’re on a journey to advance and democratize artificial intelligence through open source and open science.

HuggingFace's platform is a resource for developers and researchers working in natural language processing (NLP) and machine learning, offering insights into NLP models, tools, and datasets. Through articles, tutorials, and open-source projects, HuggingFace offers insights into state-of-the-art NLP techniques, transformer architectures, and transfer learning methods. Developers can learn about using pre-trained models, fine-tuning strategies, and deploying NLP applications with HuggingFace's libraries and APIs.

Hugging Face

Hugging Face and Cerebras have built a real-time speech-to-speech pipeline that significantly reduces voice AI latency. The open, modular architecture chains Nvidia's Parakeet for speech recognition, Google DeepMind's Gemma 4 31B for language model inference running on Cerebras hardware, and Alibaba's Qwen3TTS for text-to-speech output. Cerebras addresses the long-tail latency problem — where P95 delays make conversations feel unreliable — by providing fast, stable LLM inference. The same pipeline already powers over 9,000 Reachy Mini robots. Every component is open and replaceable, allowing developers to adapt the stack for assistants, robots, or research.

Hugging Face and Cerebras bring Gemma 4 to real-time voice AI

Architecture: an Open, Cascaded Speech-to-Speech stack