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 發布技術教學,介紹如何在 Inference Endpoints 上部署語音對語音(Speech-to-Speech, S2S)模型。透過自訂 EndpointHandler 與串流(Streaming)技術,開發者可以實現低延遲的即時語音互動。本文以開源的 Mini-Omni 模型為例,展示了從環境設定、撰寫自訂推論邏輯到部署至 GPU 節點的完整流程。